Sargur Srihari

Curriculum vitae

Sargur N. Srihari

SUNY Distinguished Professor University at Buffalo, The State University of New York Department of Computer Science and Engineering Buffalo, NY 14260, USA Mobile: (716) 984-7258 E-mail: [email protected]

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Curriculum vitae

Sargur N. Srihari

Contents

1 Personal Information ...... 3

2 Education ...... 3

3 Academic Positions ...... 3

4 Advisory Positions ...... 3

5 Honors and Awards ...... 4

6 Professional Activities ...... 5

7. Research Impact. .…………………………………………………………..……………….6

8. Teaching Impact. …………………………………………………………………….………8

9. Publications ...... 9

9.1 Journal Articles ...... 9 9.2 Books……………………………………………………………………………………..11 9.3 Book Chapters……………………………………………………………………………12 9.4 Papers in Conference Proceedings...……………………………………………………...13 9.5 Patents……………………………………………………………………………………24 9.6 Abridged Papers/Abstracts ...... 24

10. Grants and Contracts as Principal Investigator………………………………………………26

11. Doctoral Dissertations Supervised ...... 29

12. Invited Lectures and Conference Presentations……………………………………………. 31

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Sargur N. Srihari 1. PERSONAL

Born: May 7, 1950 Contact: Dept. of CSE, University at Buffalo, Davis Hall, Buffalo NY 14260 Email: [email protected] Phone: 716-645-6162

2. EDUCATION

Ph.D., 1976: Computer & Information Science, The Ohio State University, Columbus, Ohio M.S., 1972: Computer & Information Science, The Ohio State University, Columbus, Ohio B.E., 1970: Electrical Communication Engineering, Indian Institute of Science, Bangalore, India B.Sc., 1967: Physics & Mathematics, Bangalore University, Bangalore, India

3. ACADEMIC POSITIONS

2020: Satish Dhawan Visiting Chair Professor, Indian Institute of Science, Bangalore, India 2018: Rukmini Gopalakrishnachar Chair Professor, Indian Institute of Science, Bangalore, India 1997-Present: SUNY Distinguished Professor, University at Buffalo, The State University of New York Department of Computer Science and Engineering, Adjunct Professor, Department of Electrical Engineering, Adjunct Professor, Department of Biostatistics 1991-Present: Director, Center of Excellence for Document Analysis and Recognition (CEDAR) 1991-1997: Pattern Recognition Professor, Computer Science, SUNY at Buffalo 1987-1991: Professor, Computer Science, SUNY at Buffalo 1987-1988: Acting Chairman, Computer Science, SUNY at Buffalo 1982-1987: Associate Professor, Computer Science, SUNY at Buffalo 1978-1982: Assistant Professor, Computer Science, SUNY at Buffalo 1976-1978: Assistant Professor, Computer Science, Wayne State University, Detroit, MI 1970-1975: Research Assistant, Computer and Inform Sci, The Ohio State University Columbus, O

4. ADVISORY POSITIONS

National (Government) 2014-2018: Member City of Houston Forensics Technology Advisory Group 2015-2018: Member Expert Working Group on Human Factors in Handwriting Examination, NIST/NIJ 2008-2011: Member Expert Working Group on Human Factors in Latent Print Analysis, NIST/NIJ 2007-2008: Member National Academy of Sciences/National Research Council Committee on Identifying the Needs of the Forensic Science Community 2002-2007: Member, Board of Scientific Counselors, National Library of Medicine Corporate 2005-2014: Member, Board of Janya, Inc. 2000-2005: Member, Technical Advisory Board, Cymfony, Inc. 1996-Present: Chairman, Cedartech, Inc. University (External)

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2010-2012: External Evaluator, School of Computer Science, University of Putra, Malaysia 2006: Queens College, City University of New York, Comp. Science Department Evaluation Committee

5. HONORS AND AWARDS

Professional Societies Outstanding Achievements Award, ICDAR-IAPR, 2011 Fellow, International Association for Pattern Recognition, 1996 Fellow, Institute of Electrical and Electronics Engineers, 1994 Fellow, Institution of Electronics and Telecommunications Engineers, India, 1989

University Awards University at Buffalo Excellence in Graduate Mentoring Award, 2018 SUNY Outstanding Inventor Award, SUNY Research Foundation, SUNY, 2002 Distinguished Alumnus, College of Engineering, The Ohio State University, 1999 New York State United University Professions Excellence Award for 1990-91 National Merit Scholarship, India (Awarded to B.Sc rank holders), 1967-70

Paper Best Presentation Paper Award, 7th Intl Conf. Doc. Analysis and Recog., Edinburgh, Scotland, 2003

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6. PROFESSIONAL ACTIVITIES

CONFERENCES AND WORKSHOPS General Chair, International Workshop on Computational Forensics, National Academy of Sciences Keck Center, Washington D.C., 2008 General Chair, Eighth Intl.. Workshop on Frontiers in Handwriting Recognition, Niagara-on-the-lake, Ontario, Canada, 2002 General Chair, Fifth Intl. Conference on Document Analysis and Recognition, Bangalore, India, 1999 General Co-chair, Third Intl. Conference on Document Analysis & Recognition, Montreal, Canada, 1995 General Chair, Third Intl. Workshop on Frontiers of Handwriting Recognition, Buffalo, NY, 1993 Program Co-chair, First Intl. Conference on Document Analysis & Recognition, St. Malo, France 1991

SOCIETIES Publicity and Publications Committee Chair and Web Editor, Int. Assoc. for Pattern Recognition (IAPR), 2002--2008 Chairman, Technical Committee on Text Processing (TC-11), International Association of Pattern Recognition 1986-1988 Member--Association for Computing Machinery, American Association for Artificial Intelligence, Institute of Electrical and Electronics Engineers, American Association for the Advancement of Science

EDITORSHIPS Member of Editorial Board, Frontiers of Computer Science in China, 2007-2010 Associate Editor, Pattern Recognition Journal, 1982-2002 Editor-in-Chief, International Journal of Document Analysis and Recognition, 1997-2004 International Journal of Pattern Recognition and Artificial Intelligence, 1992-1996

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7. RESEARCH IMPACT STATEMENT

Srihari’s research career spans five decades. A career focusing on artificial intelligence, beginning with statistical pattern recognition and culminating in deep learning. He has contributed to the methodology of these fields, while also drawing motivation from two application areas of broad societal interest: • Document image analysis • Forensics.

Srihari’s first major papers were in representation of three-dimensional images, such as those produced in computing tomography. His ACM Computing Surveys article on the topic was influential, with citations even to this day in 3-D printing. His work with his first PhD student , on hyper-quad trees for multi-dimensional images, was published in CACM and featured on its cover

Srihari’s first external research funding was from the National Science Foundation (NSF). It was for the study of the role of context in recognizing text. At its successful conclusion (resulting in a paper in IEEE-PAMI), he approached the United States Postal Service (USPS) for funding as there was potential use of his research in address reading machines. USPS provided him with a small ($100K) grant to study existing printed address reading technology. This eventually led to large-scale funding from the United States Postal Service for several ancillary projects: • Determining address blocks on letters, flats and irregular parcels, • Reading poor quality printed addresses and • Reading handwritten addresses. This work culminated in his group being recognized as a USPS Center of Excellence for Document Analysis and Recognition, known as CEDAR. The center’s work eventually involved more than a dozen projects and more than a hundred of graduate students and a dozen full-time research staff, with funding exceeding $60 million over 25 years. The work of CEDAR received worldwide attention.

Among the more impactful work at CEDAR were: • Handwritten digit recognition was recognized as the fruit-fly of AI and machine learning. The USPS data set collected in Buffalo was succeeded by the more widely used MNIST digits. • Document analysis and recognition was recognized as an important application area of pattern recognition and machine learning, spawning several conferences and a journal. • The first large-scale handwritten address interpretation systems in the world was deployed by the USPS, eventually allowing reading over 90% of the handwritten US mail. This work is exhibited in the National Postal Museum in Washington DC. The work received worldwide attention including features on Beyond 2000(Australia), CNN, ABC News with Peter Jennings, Discovery Channel, etc. • Name and address block reader (NABR) or the Internal Revenue Service (to read off of 1040EZ) • Handwritten address readers for UK Royal Mail and for Australia Post.

Over the next decade, Srihari turned his research focus to forensic science. The National Institute of Justice (NIJ) contacted him about the need for a scientific basis for continuing to allow impression evidence such as handwriting to be presented as evidence in the courts. Srihari’s first effort with funding from the NIJ was on quantifying the individuality of handwriting. A resulting paper in the Journal of Forensic Sciences was hailed by the community of questioned document examiners as providing a basis for admitting handwriting evidence in several cases. Srihari testified in several “Daubert hearings”, April 16, 2020 6

Sargur Srihari including at the federal level, as to whether handwriting could be admitted as evidence.

The handwriting work led to the first automated system, known as CEDAR-FOX—for determining whether two handwritten samples came from the same or different writer. It was issued a United States Patent. Srihari formed a company CEDARTECH to commercialize CEDAR-FOX. Srihari and CEDAR- FOX were featured in a NOVA episode on PBS regarding the Lindbergh kidnapping.

Srihari extended his studies on comparing handwriting to comparing fingerprints and footwear prints. As a consequence of his forensic work, Srihari was invited to serve on a prestigious National Academy of Sciences Committee on Identifying the Needs of the Forensic Science Community. Srihari was the only computer scientist on this committee, which was headed by a Federal Appeals Court Judge Harry Edwards. The report has had a major impact on courts worldwide and received a prestigious award by the Innocence Project.

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8. TEACHING IMPACT STATEMENT

Srihari has been teaching courses in artificial intelligence, pattern recognition and machine learning over four decades. He has developed an extensive set of lecture slides covering several topics on • Introductory Machine Learning. • Deep Learning • Probabilistic Graphical Models

His lecture slides and videos are widely used in courses around the world. All three courses are listed in "Ten Free Top-Notch Machine Learning Courses" of the influential site KDNuggets.

Srihari has conducted numerous tutorials on the use of CEDAR-FOX, a software system for handwriting comparison. This software was widely known to the forensic community and a several tutorials were conducted, including one organized by the National Forensic Science Technology Center. Some of the others were at different meetings of the Questioned Document Examination community (ASQDE, SWAFDE, etc).

Srihari’s current teaching efforts are focused on integrating the avalanche of research being produced in deep learning—available in books, papers and blogs. He is currently video recording his explanation of topics in deep learning on Zoom and livestreaming on Facebook. His recent lectures on topics such as attention models and recommender systems have received over a thousand views each.

Srihari has served as principal advisor to 41 PhD students and hundreds of MS students. The most financially successful of these has been • Yanhong Robin Li, who founded the search engine giant Baidu and became the first Chinese billionaire. Among the more notable of Srihari’s PhD students are • Tin Kam Ho, who invented Random Forests, an important classification method. She served as Distinguished Scientist at Lucent Bell Labs. • Jonathan Hull, who holds a record number of United States Patents (over a hundred). He served for several decades as a principal research scientist at Ricoh Silicon Valley • Venugopal Govindaraju, who is a Distinguished Professor and Vice President of Research at the University at Buffalo • Dar-Shyang Lee, who has made important contributions to deep learning at Google

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9. PUBLICATIONS

The following are a list of about 400 published papers in the pattern recognition, machine learning and artificial intelligence literature. Google Scholar indicates over 19,000 citations with a h-index of 62.

9.1 Journal Articles

1. S. N. Srihari, L. Meng and L. Hanson, “Development of Handwriting Individuality in Children,” Journal of Forensic Sciences, October 2016. 2. A. Farasat, A. Nikolaev, S. N. Srihari and R.Blair, “Probabilistic Graphical Models in Modern Social Network Analysis,” Social Network Analysis and Mining, 5(1), 62:1-62:18, Springer, 2015. 3. Y. Tang and S. N. Srihari, “Likelihood Ratio Estimation in Forensic Identification using Similarity and Rarity,” Pattern Recognition, 47(3), 945-958, 2014. 4. S. N. Srihari and K. Singer. “Role of Automation in the Examination of Handwritten Items,” Pattern Recognition, 47(3), 1083-1095, 2014. 5. Y. Tang, H. Kasiviswanathan and S. N. Srihari, An efficient clustering-based retrieval framework for real crime scene footwear marks. International Journal of Granular Computing, Rough Sets and Intelligent Systems, 2012; 2 (4): 327- 360. 6. S. N. Srihari, “Computing the Scene of a Crime,” IEEE Spectrum (Invited paper), 12(47), 2010: 38-43. 7. S. N. Srihari and H. Srinivasan, "Comparison of ROC and Likelihood Decision Methods in Automatic Fingerprint Verification," International Journal of Pattern Recognition and Artificial Intelligence, 22(3), 2008: 535-553. 8. S. N. Srihari, C. Huang, H. Srinivasan and V. Shah, "On the Discriminability of the Handwriting of Twins," Journal of Forensic Sciences, 53(2), 2008: 430-446. 9. S. N. Srihari, J. Collins, R. K. Srihari, H. Srinivasan, S. Shetty and J. Brutt-Giffler, “Automatic scoring of short handwritten essays in reading comprehension tests,” Artificial Intelligence, 172 (2008): 300-324. 10. S. N. Srihari, H. Srinivasan, and G. Fang, "Discriminability of the Fingerprints of Twins," Journal of Forensic Identification, 58(1), 2008: 109-127. 11. S. N. Srihari, X. Yang and G. R. Ball, "Offline Chinese Handwriting Recognition: An Assessment of Current Technology," Frontiers of Computer Science in China, 1(2), 2007: 137-155. 12. S. N. Srihari, H. Srinivasan and K. Desai, "Questioned Document Examination using CEDAR-FOX,"Journal of Forensic Document Examination, 18, 2007, pp. 1-20. 13. S. N. Srihari, H. Srinivasan, C. Huang and S. Shetty, "Spotting Words in Latin, Devanagari and Arabic Scripts," Vivek: Indian Journal of Artificial Intelligence, 16(3), 2006: 2-9. 14. B. Zhang and S. N. Srihari, "Handwriting Identification using MultiScale Features," Journal of Forensic Document Examination, Vol. 16, Fall 2004: 1-20. 15. M. K. Kalera, S. N. Srihari and A. Xu, "Offline signature verification and identification using distance statistics," International Journal of Pattern Recognition and Artificial Intelligence, 18(7), 2004: 1339-1360. 16. Zhang, B. and S. N. Srihari, "Fast nearest neighbor classification using cluster-based trees,"IEEE Transactions on Pattern Analysis and Machine Intelligence: 26(4), 2004: 525-528. 17. Srihari, S. N., “Author’s Response to Saks’ critique,” Journal of Forensic Sciences, July 2003, 48(4): pp. 919-920. 18. Srihari, S. N. S.-H. Cha, H. Arora, and S. Lee, "Individuality of Handwriting," Journal of Forensic Sciences, 47(4), 2002: 856-872. 19. Cha, S.-H., and S. N. Srihari, "A Fast Nearest Neighbor Search Algorithm by Filtration, Pattern Recog., 35(2), 2002: 515- 525. 20. Park, J., V. Govindaraju and S. N. Srihari, “OCR in a Hierarchical Feature Space,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(4), 2000: 400-407. 21. Plamondon, R., and S. N. Srihari, “On-line and Off-line Handwriting Recognition: A Comprehensive Survey,” IEEE Transactions on Pattern Analysis and Recognition, 22(1), 2000: 63-84. 22. Srihari, S. N., “Handwritten Address Interpretation: A Task of Many Pattern Recognition Problems,” International Journal of Pattern Recognition and Artificial Intelligence, 14(5), 2000: 663-674. 23. Wang, X., V. Govindaraju and S. N. Srihari, “Holistic Digit Pair Recognition,” Pattern Recognition, 33(12), 2000: 1967- 1974.

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24. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “A Methodology for Mapping Scores to Probabilities,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(9), 1999: 923-927. 25. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “Postprocessing Recognition of Strings Using Nonstationary Markovian Models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(10), 1999: 990-999. 26. Kim, G., V. Govindaraju and S. N. Srihari, “An Architecture for Handwritten Text Recognition Systems,” International Journal of Document Analysis and Recognition, 2(1), 1999: 37-44. 27. Liu, Y., and S. N. Srihari, “Document Image Binarization Based on Texture Features,” IEEE Transactions on Pattern Recognition and Machine Intelligence, 19(5), 1997: 540-544. 28. Srihari, S. N., T. Hong and G. Srikantan, “Machine-printed Japanese Document Recognition,” Pattern Recognition, 30(8), 1997: 1301-1313. 29. Madhvanath, S., V. Govindaraju and S. Srihari, “Reading Handwritten Phrases on U.S. Census Forms,” International Journal of Imaging Systems and Technology, 7, 1996: 312-319. 30. Niyogi, D., and S. N. Srihari, “An Integrated Approach to Document Decomposition and Structural Analysis,” International Journal of Imaging Systems and Technology, 7, 1996, 330-342. 31. Palumbo, P. W., and S. N. Srihari, “Postal Address Reading in Real Time,” International Journal of Imaging Systems and Technology, 7, 1996: 370-378. 32. Srihari, S. N., Y.-C. Shin, V. Ramanaprasad and D.-S. Lee, “A System to Read Names and Addresses on Tax Forms,” Proceedings of IEEE, 84(7), 1996, pp. 1038-1049. 33. Srihari, S. N., Y.-C. Shin, V. Ramanaprasad and Z. Shi, “Document Image-processing System for Name and Address Recognition,” International Journal of Imaging Systems and Technology, 7, 1996: 379-391. 34. Chen, M. Y., A. Kundu and S. N. Srihari, “Variable Duration Hidden Markov Model and Morphological Segmentation of Handwritten Words,” IEEE Transactions on Image Processing, 4(12), 1995: 1675-1688. 35. Cohen, E., J. J. Hull and S. N. Srihari, “Control Structure for Interpreting Handwritten Addresses,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(10), 1994: 1049-1055. 36. Ho, T. K., J. J. Hull and S. N. Srihari, “Decision Combination in Multiple Classifier Systems,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(1), 1994: 66-75. 37. Wang, D., and S. N. Srihari, “Analysis of Form Images,” International Journal of Pattern Recognition and Artificial Intelligence, 8(5), 1994, pp. 1031-1052. 38. Chen, J. S., and S. N. Srihari, “Hypothesis Generation in Conflict-based Diagnosis,” International Journal of Pattern Recognition and Artificial Intelligence, 7(3), 1993: 465-492. 39. Srihari, S. N., “Recognition of Handwritten and Machine-printed Text for Postal Address Interpretation,” Pattern Recognition Letters, 1993: 291-302. 40. Ho, T. K., J. J. Hull and S. N. Srihari, “A Computational Model for Recognition of Multi-font Word Images,” Machine Vision and Applications, 5(1), 1992: 157-168. 41. Ho, T.K., J.J. Hull and S.N. Srihari, “Multiclassifier Approach to Word Recognition,” Pattern Recognition Letters, 1992. 42. Ho, T. K., J. J. Hull and S. N. Srihari, “Word-Shape Analysis Approach to Lexicon-Based Word Recognition,” Pattern Recognition Letters, 1992: 821-826. 43. Palumbo, P. W., S. N. Srihari, J. Soh, R. Sridhar and V. Demjanenko, “Postal Address Block Location in Real-time,” IEEE Computer, 25(7), 1992: 33-45. 44. Shin, Y.-C., R. Sridhar, V. Demjanenko, P. W. Palumbo and S. N. Srihari, “A Special-Purpose Content Addressable Memory Chip for Real-time Image Processing,” IEEE Journal of Solid State Circuits, 27(5), 1992: 737-744. 45. Srihari, S. N., "High Performance Reading Machines, Proceedings of IEEE, 80(7), 1992: 1120-1132. 46. Cohen, E., J. J. Hull and S. N. Srihari, “Understanding Text in a Structured Environment: Determining ZIP Codes from Addresses,” International Journal of Pattern Recognition and Artificial Intelligence, 5(1 & 2), 1991: 221-264. 47. Bozinovic, R., and S. N. Srihari, “Off-line Cursive Script Word Recognition,” IEEE Transactions on Pattern Analysis Machine Intelligence, 11(1), 1989: 68-83. 48. Soh, J., P. W. Palumbo and S. N. Srihari, “Towards Developing a Real-time System for Address Block Location,” International Journal of Research and Engineering—Postal Applications, 1(1), 1989: 57-76. 49. Srihari, S. N., E. Cohen, J. J. Hull and L. Kuan, “A System to Locate and Recognize ZIP Codes in Handwritten Addresses,” International Journal of Research & Engineering—Postal Applications, 1(1), 1989, pp. 37-56. 50. Srihari, S. N., and V. Govindaraju, “Analysis of Textual Images Using the Hough Transform,” Machine Vision and Applications, 2, 1989: 141-153. 51. Srihari, S. N., and Z. Xiang, “Spatial Knowledge Representation,” International Journal of Pattern Recognition and Artificial Intelligence, 3(1), 1989: 67-84. 52. Wang, D., and S. N. Srihari, “Classification of Newspaper Image Blocks Using Texture Analysis,” Computer Vision, Graphics and Image Processing, 47, 1989: 327-352.

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53. Wang, C.-H., and S. N. Srihari, “A Framework for Object Recognition in a Visually Complex Environment and Its Application to Locating Address Blocks on Mail Pieces,” International Journal of Computer Vision, 2, 1988: 119-145. 54. Sheikholeslami, G., S. N. Srihari, and V. Govindaraju, “Computer-aided Graphology and Persian Handwriting,” Computer Magazine, 9 (61), 1998, (in Arabic). 55. Bozinovic, R.M. and S.N. Srihari, “A Multilevel Perception Approach to Cursive Script Recognition,” Artificial Intelligence Journal, 33(2), 1987: 217-255. 56. Palumbo, P. W., and S. N. Srihari, “Text Parsing Using Spatial Information for Recognizing Addresses in Mail Pieces,” Electro Technology: Journal of the Society of Electronic Engineers of India, XXXI (1 & 2), 1987: 28. 57. Srihari, S. N., C.-H. Wang, P. W. Palumbo and J. J. Hull, “Address Block Location: Specialized Tools and Problem- Solving Architecture,” AI Magazine, Winter 1987, pp. 25-40. (Cover feature for this issue.) 58. Chutkow, J. G., S. C. Shapiro, S. N. Srihari and Z. Xiang, “Computerized Neurological Diagnosis: A Paradigm of Modeling and Reasoning,” Health Care Instrumentation, 1985: 90-105. 59. Hardas, D., and S. N. Srihari, “Progressive Refinement of 3-D Images Using Coded Binary Trees: Algorithms and Architecture,” IEEE Transactions on Pattern Analysis Machine Intelligence, 6(6), 1984: 748-757. 60. Srihari, S. N., “Pyramid Representations for Solids,” Information Sciences, 34, 1984, pp. 25-46. 61. Hull, J. J., S. N. Srihari and R. Choudhari, “An Integrated Algorithm for Text Recognition: Comparison with a Cascaded Algorithm,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 5(4), 1983: 384-395. 62. Srihari, S. N., J. J. Hull and R. Choudhari, “Integrating Diverse Knowledge Sources in Text Recognition,” ACM Transactions on Office Information Systems, 1(1), 1983, pp. 68-87. (Reviewed in Computing Reviews, 1983.) 63. Yau, M., and S. N. Srihari, “A Hierarchical Data Structure for Multidimensional Digital Images,” Communications of the ACM, 26(7), 1983: 504-515. (Cover feature for this issue.) 64. Bozinovic, R., and S. N. Srihari, “String Correction Algorithm for Cursive Script Recognition,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 4(6), 1982: 655-663 (corresp.). 65. Hull, J. J., and S. N. Srihari, “Experiments in Text Recognition with Binary N-gram and Viterbi Algorithms,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 4(5), 1982, pp. 520-530 (corresp.). 66. Srihari, S. N., “Reliability Analysis of Biased Majority-vote Systems,” IEEE Transactions on Reliability, 31(1), 1982: 117-118. 67. Srihari, S. N., “Reliability Analysis of Majority-vote Systems,” Information Sciences, 26, 1982, pp. 243-256. 68. Udupa, J. K., S. N. Srihari and G. T. Herman, “Boundary Detection in Multidimensions,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 4(1), 1982: 41-50. 69. Srihari, S. N., “Representation of Three-dimensional Digital Images,” ACM Computing Surveys, 13(4), 1981: 399-424. 70. Srihari, S. N., “On Choosing Measurements for Invariant Pattern Recognition,” Inform. Sciences, 21(1), 1980: 1-11. 71. Srihari, S. N., T. Snabb and L. J. White, “An Algorithm for Determining Identity of Nearest-neighbor and Potential Function Decision Rules,” Pattern Recognition, 12(5), 1980: 293-299. 72. Srihari, S. N., “Recursive Implementation of a Two-step Nonparametric Decision Rule,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 1(1), 1979: 90-94 (corresp.). 73. Srihari, S. N., and M. K. Ohanesian, “An Efficient Algorithm for Determining Hadamard Sequency Vectors,” IEEE Transactions on Computers, (3), 1979: 243-244 (corresp.). 74. Srihari, S. N., “Feature-ordering Criteria for Composite Classes Arising in Invariant Pattern Recognition,” IEEE Transactions on Systems, Man & Cybernetics, 8(7), 1978: 556-561 (corresp.).

9.2 Books

1. A. K. Muda, Y-H Choo, A. Abraham and S. N. Srihari (Eds.) Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, Springer, Studies in Computational Intelligence 555, 2014, 452 pages. 2. Taylor, M. K.; Kaye, D. H.; Busey, T.; Gische, M.; LaPorte, G.; Aitken, C.; Ballou, S. M.; Butt, L.; Champod, C.; Charlton, D.; Dror, I. E.; Epstein, J.; Garrett, R. J.; Houck, M.; Imwinkelried, E. J.; Keaton, R.; Langenburg, G.; Leben, D. A.; Maceo, A.; Martin, K. F.; Mnookin, J. L.; Neumann, C.; Polski, J.; Roberts, M. A.; Shappell, S. A.; Shaver, L.; Srihari, S. N.; Stern, H. S.; Stoney, D.; Swienton, A.; Theofanos, M. F.; Thompson, R. M.; Vanderkolk, J.; Weir, M.; Wertheim, K. Latent Print Examination and Human Factors: Improving the Practice through a Systems Approach, NIST Interagency/Internal Report (NISTIR) - 7842, 2012. 3. S. N. Srihari and K. Franke, Eds., Computational Forensics, Springer, LNCS 5158, 2008. 4. S. N. Yanushkevich, P. S. P. Wang, M. L. Gavrilova and S. N. Srihari, Eds., Image Pattern Recognition: Synthesis and Analysis in Biometrics, World Scientific, 2007. 5. Srihari, S. N.,Computer Text Recognition and Error Correction: A Tutorial, IEEE Computer Society Press, 1984, 363 pp. (ISBN 0-8186-0579-0). April 16, 2020 11

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9.3 Book Chapters

1. S. N. Srihari, "Probabilistic Graphical Models," in Encyclopedia of Social Network Analysis and Mining (ESNAM), Second Edition, R. Alhajj and J. Rokne, eds., Springer, 2017. 2. S. N. Srihari, "Synthetic Data Sets," in Encyclopedia of Social Network Analysis and Mining (ESNAM), R. Alhajj and J. Rokne, eds., Springer, 2017. 3. S. N. Srihari and Y. Tang, "Computational Methods for the Analysis of Footwear Evidence,' in Computational Intelligence in Digital Forensics, A. Muda, Y-H. Choo, A. Abraham and S. N. Srihari (eds.), Springer 2014, 333-383. 4. S. N. Srihari, “Probabilistic Graphical Models,” in Encyclopedia of Social Network Analysis and Mining, R. Alhajj and J. Rokne (eds.), Springer 2013. 5. S. N. Srihari and G. R. Ball, "An Assessment of Arabic Handwriting Recognition Technology," in V. Margner and H. El Abed (Eds.), Guide to OCR for Arabic Scripts , Springer 2012, pp. 3-34 6. C. Su and S. N. Srihari, “ Generative Models and Probability Evaluation for Forensic Science,” Pattern Recognition, Biometrics and Machine Intelligence, P. Wang, Springer 2011. 7. H. Srinivasan and S. N. Srihari, "Use of Conditional Random Fields for Signature-based Retrieval of Scanned Documents," in Computational Methods for Counterterrorism, S. Argamon & N. Howard (eds). Springer, 2009, 17-32. 8. S. N. Srihari, H. Srinivasan and M. Beal, "Machine Learning for Signature Verification," in Machine Learning in Document Analysis and Recognition. S. Marinai and H. Fujisawa (eds.), Springer Series: Studies on Computational Intelligence, vol. 90, 2008, pp. 387-408. 9. S. N. Srihari, G. R. Ball and H. Srinivasan,”Versatile Search of Scanned Arabic Handwriting,” in Arabic and Chinese Handwriting Recognition, D. Doermann and S. Jaeger (eds.), LNCS 4768, Springer 2008, pp. 57-69. 10. S. N. Srihari, C. Huang, H. Srinivasan and V. A. Shah, “Biometric and Forensic Aspects of Digital Document Processing”, in Digital Document Processing, B. B. Chaudhuri (ed.), Springer, 2006. 11. Srihari, S.N., “Handwriting Recognition, Automatic”, in Encyclopedia of Language and Linguistics, 2nd Ed, Elsevier, 2006. 12. Cha, S.-H., and S. N. Srihari, "Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition," Pattern Recognition: From Classical to Modern Approaches, S. K. Pal and A. Pal (eds), World Scientific, 2001,559-574. 13. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Address Interpretation,” Mail Technology–Tomorrow’s World: Business Opportunities and Solutions in a Global Market, ImechE, 1999, pp. 147-156. 14. Niyogi, D., S. N. Srihari and V. Govindaraju, “Analysis of Printed Forms,” Handbook of Character Recognition and Document Image Analysis, H. Bunke and P. S. P. Wang, eds., World Scientific Publishing, 1997, pp. 485-502. 15. Srihari, S. N., G. Srikantan, T. Hong and S. W. Lam, “Research in Japanese OCR,” Handbook of Character Recognition and Document Image Analysis, H. Bunke and P. S. P. Wang, eds., World Scientific, 1997, pp. 357-378. 16. Srihari, S. N., T. Hong and G. Srikantan, “Japanese Optical Character Recognition,” Handbook of Document Image Analysis, H. Bunke and P. S. P. Wang, eds., World Scientific Publishing, 1996. 17. Srihari, S. N., and R. K. Srihari, “Written Language Recognition,” NSF-CEC Joint Survey on Speech and Natural Language Processing, 1996, pp. 69-74. 18. Govindaraju, V., R. K. Srihari and S. N. Srihari, “Handwritten Text Recognition,” Document Analysis Systems, A. L. Spitz and A. Dengel eds., World Scientific Publishing, 1995, pp. 288-306. 19. Srihari, S. N., S. W. Lam and J. J., Hull, “Document Recognition for Digital Library,” Digital Libraries, N. R. Adam, B. K. Bhargava, and Y. Yesha , eds., Springer-Verlag, 1995, pp. 119-128. 20. Fenrich, R., S. Lam and S. N. Srihari, “Optical Character Recognition,” Encyclopedia of Computer Science and Engineering, A. Ralston, ed., third edition, Van Nostrand, 1992, pp. 993-1000. 21. Srihari, S. N., and V. Govindaraju, “Pattern Recognition,” Encyclopedia of Computer Science and Engineering, A. Ralston, ed., third edition, Van Nostrand, 1992, pp. 1034-1041. 22. Srihari, S. N., and J. J. Hull, “Character Recognition,” Encyclopedia of Artificial Intelligence, S. C. Shapiro, ed., second edition, Wiley, 1992, pp. 138-150. 23. Lee, D. S., S. N. Srihari and R. Gaborski, “Bayes and Neural Network Pattern Recognition: A Theoretical Connection and Empirical Results with Handwritten Digits,” Artificial Neural Networks and Statistical Pattern Recognition, I. S. Sethi and and A. K. Jain, eds., North-Holland, 1991, pp. 89-108. 24. Srihari, S. N., “High-performance Reading Machines,” Pattern Recognition: Architecture, Algorithms and Applications, R. Plamondon and H. D. Cheng, eds., World Scientific Publishing, 1991, pp. 271-300. 25. Srihari, S. N., “Applications of Expert Systems in Engineering: An Overview,” Knowledge-Based System Diagnosis, Supervision, and Control, S. G. Tzafestas, ed., Plenum Press, 1989, pp. 1-10. 26. Srihari, S. N., “Feature Extraction for Address Block Location,” From Pixels to Features, J. C. Simon, ed., North Holland, 1989, pp. 261-274. April 16, 2020 12

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27. Srihari, S. N., “The Viterbi Algorithm,” Encyc. of Artificial Intelligence, S. C. Shapiro, ed., Wiley, 1987, 1160-1162. 28. Srihari, S. N., “Multiresolution Representations for 3-D Image Processing and Graphics,” Multiresolution Image Processing and Analysis, A. Rosenfeld, ed., Springer-Verlag, 1983, pp. 224-236. 29. Jernigan, M. E., and S. N. Srihari, “Pattern Recognition,” Encyclopedia of Computer Science, A. Ralston, ed., second edition, Van Nostrand Reinhold, 1982, pp. 1110-1119. 30. Altschuler, M. D., Y. Censor, G. T. Herman, A. Lent, R. M. Lewitt, S. N. Srihari, H. Tuy and J. K. Udupa, “Mathematical Aspects of Image Reconstruction from Projections,” Progress in Pattern Recognition, L. Kanal and A. Rosenfeld, eds., North-Holland, 1981, pp. 323-375.

9.4 Papers in Conference Proceedings

1. T. Duan, Q. Lou, S. N. Srihari, X. Xie, “Sequential embedding induced text clustering: a nonparametric Bayesian approach,” in Proc. Pacific Asia Conf. on Knowledge Discovery and Data Mining (PAKDD), Macau, China, 2019. 2. J. Chu, M. A. Shaikh, M. Chauhan, L. Meng, S. N. Srihari, “Writer verification using CNN feature extraction,” in Proc. Int. Conf. Frontiers of Handwriting Recognition (ICFHR), Niagara Falls, NY 2018, 181-186. 3. M. A. Shaikh, M. Chauhan, J. Chu , S. N. Srihari, “Hybrid feature learning for writer verification,” in Proc. Int. Conf. Frontiers of Handwriting Recognition (ICFHR), Niagara Falls, NY 2018, 187-192. 4. T. Duan and S. N. Srihari, "Layerwise interweaving convolutional LSTM, in Proc. Canadian Conference on Artificial Intelligence, 2017. 5. Z. Xu, S.N. Srihari and W. Dong, “Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model”, in Proc. Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016. 6. T. Duan and S. N. Srihari, “Pseudo-boosted Deep Belief Network,” in Proc. 25th Int. Conf. Artificial Neural Networks, Barcelona, Spain, 2016. 7. Z. Xu and S. N. Srihari, "Missing Value Imputation: Application to Handwriting Data," in Proc. Document Recognition and Retrieval XXII, San Francisco, CA, 2015. 8. G. Fang and S. N. Srihari, “Removing Structural Noise in Handwriting Images using Deep Learning,” in Proc. Int. Conf. Computer Vision, Graphics and Image Processing, Bangalore, India, 28:1-28:8, 2014. 9. G. Fang and S. N. Srihari,"A Noisy-Or Discriminative Restricted Boltzmann Machine for Recognizing Handwriting Style Development," Proc. Int. Conf. Handwriting Recognition, Crete, Greece, 714-719, 2014. 10. S. N. Srihari and Z. Xu, “Development of Handwriting Individuality: An Information-Theoretic Study,” in Proc. Int. Conf. Handwriting Recognition, Crete, Greece, pp. 601-606, 2014. 11. M. Puri, S. N. Srihari and L. Hanson, "Probabilistic Modeling of Children's Handwriting," in Proc. Document Recognition and Retrieval XXI, San Francisco, CA, Feb. 2014. 12. M. Puri, S. N. Srihari and Y. Tang, "Bayesian Network Structure Learning and Inference Methods for Handwriting," in Proc. Int. Conf. Document Analysis and Recognition, Washington DC, Aug. 2013. 13. S. N. Srihari, "Determining Writership of Historical Manuscripts using Computational Methods," in On-line Proceedings Automatic Pattern Recognition and Historical Handwriting Analysis, Erlangen, Germany, June 2013. 14. Y. L. Wong, S. M. Shamsuddin and S. N. Srihari: Fusing Modalities in Forensic Identification with Score Discretization. in AFHA 2013: 46-50, 2013. 15. S. N. Srihari, D. Kovalenko, Y. Tang and G. R. Ball, "Combining Evidence using Likelihood Ratios in Writer Verification'', in Proc. Document Recognition and Retrieval XX, San Francisco, CA, Feb. 2013. 16. D. Kovalenko and S. N. Srihari, "On Methods for Incorporating Evidences into Posterior Scoring of Hypotheses", in Proc. Int. Conf. Pattern Recognition, Tsukuba, Japan, Nov. 2012. 17. Y. Tang and S. N. Srihari. "An Efficient Algorithm for Learning Bayesian Networks for Multinomials," in Proc. Int. Conf. Pattern Recognition, Tsukuba, Japan, Nov. 2012. 18. S. N. Srihari and K. Singer, "Role of Automation in the Examination of Handwritten Items," in Proc. Int. Conf. Handwriting Recognition, Bari, Italy, September 2012. 19. Y. Tang, S. N. Srihari and H. Srinivasan, "Handwriting Individualization Using Distance and Rarity," in Proc. Document Recognition and Retrieval XIX, San Francisco, CA, Jan. 2012. 20. K. Das, S. N. Srihari and H. Srinivasan, "Questioned Document Workflow for Handwriting with Automated Tools," in Proc. Document Recognition and Retrieval XIX, San Francisco, CA, Jan. 2012 21. Y. Tang and S. N. Srihari, "Robust Ellipse Detection," in Proc International Conference on Image Processing, Brussels, Belgium, September 2011. 22. S. N. Srihari, “Evaluating the Rarity of Handwriting Formations,” in Proc. ICDAR, Beijing, China, September 2011. April 16, 2020 13

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23. G. R. Ball and S. N. Srihari, "Statistical Characterization of Handwriting Characteristics using Automated Tools", in Proc. Document Recognition and Retrieval, San Francisco, CA, January 2011. 24. C. Su and S. N. Srihari, "Evaluation of Rarity of Fingerprints in Forensics," in Proc Neural Information Processing Systems, Vancouver, Canada, Dec. 2010. 25. G. R. Ball, S. N. Srihari and R. Stittmeyer, "Writer Identification of Historical Documents Among Cohort Writers," in Proc Int Conference on Frontiers of Handwriting Recognition, Kolkata, India, Nov. 2010. 26. Y. Tang, S. Srihari, H. Kasiviswanathan and J. Corso, "Footwear Print Retrieval System for Real Crime Scene Marks," in Proc Int Workshop on Computational Forensics, Tokyo, Japan, Nov 11-12, 2010. 27. C. Su and S. N. Srihari. "Latent Fingerprint Rarity Analysis in Madrid Bombing Case,"in Proc International Workshop on Computational Forensics, Tokyo, Japan, Nov 11-12, 2010. 28. C. Su and S. N. Srihari, "Latent Fingerprint Core Point Prediction Based on Gaussian Processes”, in Proceedings International Conference on Pattern Recognition, Istanbul, Turkey, Aug 2010, pp. 1634-1637. 29. D. Pu and S. N. Srihari, “A Probabilistic Measure for Signature Verification based on Bayesian Learning,” in Proceedings International Conference on Pattern Recognition, Istanbul, Turkey, Aug, 2010, pp. 1188-1191. 30. G. R. Ball, S. N. Srihari and H. Kasiviswanathan,"Top Down Analysis of Line Structure in Handwritten Documents," in Proceedings International Conference on Pattern Recognition, Istanbul, Turkey, Aug, 2010. 31. G. R. Ball, R. Stittmeyer and S. N. Srihari, "Writer Verification in Historical Documents," in Proc. Document Recognition and Retrieval XVII, San Jose, CA, January 2010. 32. C. Su and S. N. Srihari, "Probability of Random Correspondence for Fingerprints," in Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009. 33. Y. Liu and S. N. Srihari, "A Computational Discriminability Analysis of Twin Fingerprints," in Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009. 34. D. Pu, G. R. Ball and S. N. Srihari, "A Machine Learning Approach to Off-Line Signature Verification using Bayesian Inference," Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009. 35. K. Manning and S. N. Srihari, "Computer-Assisted Handwriting Analysis: Interaction with Legal Issues in U. S. Courts," Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009. 36. G. R. Ball and S. N. Srihari, "Semi-supervised Learning for Handwriting Recognition," in Proc Tenth Int. Conf. on Document Analysis Recognition (ICDAR-2009), Barcelona, Spain, July 2009, IEEE Computer Society Press, pp. 29-30. 37. G. R. Ball and S. N. Srihari, "Comparison of Statistical Models for Writer Verification," in Proc Document Recognition and Retrieval XVI, San Jose, CA, January 2009, SPIE, pp. 7247OE 1-8. 38. S. N. Srihari, G. R. Ball and V. Ramakrishnan, "Identification of Forgeries in Handwritten Petitions for Ballot Propositions," Proc. Document Recognition and Retrieval XVI, San Jose, CA, January 2009, 39. C. Su and S. N. Srihari, "Generative Models for Fingerprint Individuality using Ridge Models," Proc International Conference on Pattern Recognition, Tampa, FL, 2008. 40. V. Ramakrishnan and S. N. Srihari, "Extraction of Shoeprint Patterns from Impression Evidence using Conditional Random Fields," Proc International Conference on Pattern Recognition, Tampa, FL, 2008. 41. S. N. Srihari and G. R. Ball, "Language Independent Word Spotting in Scanned Documents," Proc International Conference on Asia-Pacific Digital Libraries, Bali, Indonesia, 2008. 42. S. N. Srihari and G. R. Ball, "Writer verification of Arabic handwriting," Proc. Eighth Int. Workshop on Document Analysis Systems, Nara Japan, IEEE Computer Society Press, 2008, pp. 28-34. 43. G. R. Ball and S. N. Srihari, "Prototype Integration in Off-line Handwriting Recognition Adaptation,", Proc International Conference on Frontiers in Handwriting Recognition, Montreal, Canada, pp. 529-534. 44. K. Kuzhinjedathu, H. Srinivasan, S. N. Srihari, "A Bayesian Approach to Off-Line Signature Verification," Proceedings International Conference on Frontiers in Handwriting Recognition, Montreal, Canada, pp. 611-616. 45. K. Franke and S. N. Srihari, "Computational Forensics: An Overview,"Computational Forensics: Proc Second International Workshop, Washington D.C., 2008, Springer LNCS 5158, pp. 1-10. 46. S. N. Srihari and C. Su, "Computational Methods for Determining Individuality,"Computational Forensics: Proceedings Second International Workshop, Washington D.C., 2008, Springer LNCS 5158, pp. 11-21.pdf 47. V. Ramakrishnan, M. Malgireddy and S. N. Srihari, "Shoeprint Extraction from Latent Images using CRFs," in Computational Forensics: Proc. Second Int. Workshop, Washington D.C., 2008, Springer LNCS 5158, pp. 105-112. 48. S. N. Srihari, K. Kuzhinjedathu, H. Srinivasan and C. Huang, "Signature Verification using Bayesian Approach,"in Computational Forensics: Proc Second International Workshop , Wash. D.C., 2008, Springer LNCS 5158, 192-203. 49. C. Huang and S. N. Srihari, "Word Segmentation of Off-line Handwritten Documents," Proc. Document Recognition and Retrieval XV, San Jose, CA, SPIE Vol. 6815, January 2008, pp. 68150E-1-6. 50. G. R. Ball and S. N. Srihari, "Writer adaptation in off-line Arabic handwriting," Proc. Document Recognition and Retrieval XV, IST/SPIE Annual Symposium, San Jose, CA, Vol. 6815, January 2008, pp. 681505-1-6. 51. K. Kuzhinjedathu, H. Srinivasan and S. N. Srihari, "Robust line segmentation for handwritten documents," Proc.

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Document Recognition and Retrieval XV, San Jose, CA, SPIE Vol. 6815, January 2008, pp. 68150CC-1-9. 52. C. Huang and S. N. Srihari "Automatic Writer Verification with Handwriting of Twins and Non-Twins," Proc. International Graphonomics Society Conference Melbourne, Australia, November 2007, pp. 184-187. 53. K. Kuzhinjedathu, H. Srinivasan and S. N. Srihari, "Segmentation of Overlapping Handwritten Lines," Proc. International Graphonomics Society Conference, Melbourne, Australia, November 2007, pp. 28-31. 54. H. Srinivasan, S. Kabra, C. Huang and S. N. Srihari, "On Computing the Strength of Evidence for Writer Verification," Proc. International Conference on Document Analysis and Recognition, Curitiba, Brazil, September 2007, pp.844-848. 55. A. Bharadwaj, A. Singh, H. Srinivasan, and S. N. Srihari, "On the use of Lexeme features for writer verification," in Proc. Int. Conference on Document Analysis Recognition (ICDAR-2007), Curitiba, Brazil, Sept. 2007, pp. 1088-1092. 56. S. Shetty, H. Srinivasan, and S. N. Srihari, "Handwritten Word Recognition using Conditional Random Fields," in Proc. Int. Conference on Document Analysis Recognition (ICDAR-2007), Curitiba, Brazil, Sept. 2007, pp. 1098-1102. 57. K. Franke and S. N. Srihari, "Computational Forensics: Towards Hybrid-Intelligent Crime Investigation", Proc. Int. Symp. Information Assurance Security/ Int. Wkshop on Computational Forensics (IWCF 2007), Manchester, England, Aug. 2007, IEEE-CS Press, pp. 383-386. 58. G. Fang, H. Srinivasan and S. N. Srihari, "Use of Ridge Types in Generative Models of Fingerprint Individuality," Proc. Int. Symp. Information Assurance and Security/ Int. Wkshop Computational Forensics ( IWCF 2007), Manchester, England, Aug. 2007, IEEE-CS Press, pp. 423-428. 59. G. Fang, S. N. Srihari, H. Srinivasan, and P. Phatak, "Use of ridge points in partial fingerprint matching," in Proc. Defense Security Symp, A. Ross(ed) Proc. SPIE, Orlando, FL, April 2007, vol. 6539, pp. 65390D-1 to 65390D-9. 60. M. Arivazhagan, H. Srinivasan, and S. N. Srihari, "A Statistical Approach to Handwritten Line Segmentation", in Proc. Document Recognition and Retrieval IV, Proceedings of SPIE, San Jose, CA, February 2007, pp. 6500T-1 to 6500T-11. 61. S. Shetty, H. Srinivasan, S. N. Srihari and M. Beal, "Use of Conditional Random Fields in Document Image Retrieval," in Proc. Document Recognition and Retrieval IV, Proc. SPIE, San Jose, CA, February 2007, pp. 6500U1-6500U9. 62. S. N. Srihari, R. K. Srihari, H. Srinivasan and P. Babu, "On the Automatic Scoring of Handwritten Essays," in Proc. International Joint Conference on Artificial Intelligence(IJCAI), Hyderabad, India, Jan. 2007, pp. 2880-2884. 63. C. Huang and S. N. Srihari, "Mapping Transcripts to Handwritten Text,"Proc. International Workshop on Frontiers in Handwriting Recognition (IWFHR-10), La Baule, France, October 2006, pp. 15-20. 64. G. Ball, S. N. Srihari and H. Srinivasan, "Segmentation-Free and Segmentation-Dependent Approaches to Arabic Word Spotting," in Proc. Int. Wkshop Frontiers in Handwriting Recognition, La Baule, France, Oct. 2006, pp. 53-58. 65. S. Chen and S. N. Srihari, "Machine Print Filter for Handwriting Analysis," in Proc. International Workshop on Frontiers in Handwriting Recognition (IWFHR-10), La Baule, France, October 2006, pp. 569-573. 66. S. Chen and S. N. Srihari, "A New Off-line Signature Verification Method based on Graph Matching," Proc. International Conference on Pattern Recognition (ICPR 2006), Hong Kong, Aug. 2006. 67. S. N. Srihari, S. Shetty, S. Chen, H. Srinivasan, C. Huang, G. Agam, O. Frieder, "Document Image Retrieval using Signatures as Queries," in Proc. Second IEEE International Conference on Document Image Analysis for Libraries, Lyon, France, April 27-28, 2006, pp. 198-203. 68. H. Srinivasan, S. N. Srihari and M. Beal, "Comparison of Classification Methods for Fingerprint Verification for Variable Number of Minutiae," in Proc. Biometric Technology for Human Identification III: SPIE Defense and Security Symposium, Orlando, FL, April 17-22, 2006, pp. 620209-1 to 620209-12. 69. S. N. Srihari, J. Collins, R. K. Srihari, P. Babu and H. Srinivasan "Automatic Scoring of Handwritten Essays using Latent Semantic Analysis" Proc. Document Analysis Systems Springer, Nelson, New Zealand, Feb. 2006, pp. 71-83. 70. S. N. Srihari, H. Srinivasan, P. Babu and C. Bhole, "Spotting Words in Handwritten Arabic Documents," Proc. Document Recognition and Retrieval XIII(SPIE), San Jose, CA, January 2006, pp. 606702-1 to 606702-12. 71. S. Chen and S. N. Srihari, "Combining one- and two-dimensional signal recognition approaches to off-line signature verification," Proc. Document Recognition Retrieval XIII(SPIE), San Jose, CA, Jan. 2006, pp. 606701-1 to 606701-10. 72. S. N. Srihari, H. Srinivasan, P. Babu and C. Bhole, "Handwritten Arabic Word Spotting using the CEDARABIC Document Analysis System," Proc. Symp. Doc. Image Understanding (SDIUT 05), Nov. 2005, pp. 123-132. 73. S. Chen and S. N. Srihari, "Use of Exterior Contours and Word Shape in Off-line Signature Verification," Proc. International Conference on Document Analysis and Recognition, Seoul, Korea, August 2005, pp. 1280-1284. 74. S. N. Srihari, M. Beal, K. Bandi, V. Shah and P. Krishnamurthy, "A Statistical Model for Writer Verification," Proc. International Conference on Document Analysis and Recognition, Seoul, Korea, August 2005, pp. 1105-1109. 75. H. Srinivasan, S. N. Srihari and M. Beal, "Signature Verification using Kolmogorov-Smirnov Statistic," Proc. International Graphonomics Society Conference (IGS), June 2005, Salerno, Italy, pp. 152-156. 76. K. Bandi and S. N. Srihari, "Writer Demographic Identification using Bagging and Boosting," Proc. International Graphonomics Society Conference (IGS), June 2005, Salerno, Italy, pp.133-137. 77. H. Srinivasan, M. Beal and S. N. Srihari, "Machine Learning for Person Identification and Verification", SPIE Conf. Homeland Security, Orlando, FL, March 2005, Society of Photo Instrumentation Engineers (SPIE), 574-586.

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78. S. N. Srihari, C. Huang and H. Srinivasan, "A Search Engine for Handwritten Documents", Document Recognition and Retrieval XII, San Jose, CA, January 2005, Society of Photo Instrumentation Engineers (SPIE), pp. 66-75. 79. S. N. Srihari, C. Huang and H. Srinivasan, "Content-Based Retrieval of Handwritten Document Images," Knowledge Based Computer Systems (KBCS 2004), Hyderabad, India, December 2004, pp. 302-311. 80. A. Xu, S.N. Srihari, and M. K. Kalera "Learning Strategies for Signature Verification", Proc. Int. Workshop Frontiers in Handwriting Recognition (IWFHR 2004), Tokyo, Japan, Nov. 2004, IEEE Computer Society Press, pp. 161-166. 81. C. Tomai, B. Zhang and S. N. Srihari, "Discriminatory power of handwritten words for writer recognition," Proc. International Conference on Pattern Recognition (ICPR 2004), Cambridge, England, August 2004, pp. 638-641. 82. B. Zhang and S. N. Srihari, "Discovery of a tri-edge inequality for binary dissimilarity measures", Proc. International Conference on Pattern Recognition (ICPR 2004), Cambridge, England, August 2004, pp. 669-672. 83. Zhang, Bin, S. N. Srihari and C. Huang, “Word Image Retrieval Using Binary Features,” Document Recognition and Retrieval XI (E.H.B. Smith, J. Hu and J. Allan, eds.) SPIE, Bellingham WA, 2004, ISBN 0-8194-5199-1, pp. 45-53. 84. Tomai, Catalin, D. M. Kshirsagar and S. N. Srihari, “Group Discriminatory Power of Handwritten Characters,” Document Recognition and Retrieval XI (E.H.B. Smith, J. Hu and J. Allan, eds.) SPIE, Bellingham WA, 2004, pp. 116-123. 85. M. Kalera, B. Zhang and S. N. Srihari,” Off-line signature verification and identification using distance statistics,” Proceedings eleventh International Graphonomics Society Conf. (IGS), pp. 228-232, Nov. 2003, Scottsdale, Arizona. 86. B. Zhang, and S. N. Srihari, "Handwriting Identification using Multiscale Features," Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 270-273, November 2003, Scottsdale, Arizona. 87. A. Shekhawat, S. N. Srihari, and S. Parulekar "Individuality Studies for On-line Handwriting” Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 266-269, November 2003, Scottsdale, Arizona. 88. Z. Shi, B. Zhang, C. Tomai, and S. N. Srihari, “Recognition based system for handwriting verification and identification,” Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 261-265, Nov. 2003, Scottsdale, Arizona. 89. S. N. Srihari and G. Leedham, “A survey of computer methods in forensic document examination,” Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 278-281, November 2003, Scottsdale, Arizona. 90. B. Zhang, C. Tomai, S. Srihari and V. Govindaraju, “Construction of handwriting databases using transcript-based mapping,” Proceedings of Document Image Analsysi Digital Libraries (DIAL 2004), pp. 288-298, Palo Alto, CA, Jan. 2004. 91. S, N. Srihari and Z. Shi, Forensic Handwritten Document Retrieval System, Proceedings of Document Image Analsysi for Digital Libraries (DIAL 2004), pp. 188-194, Palo Alto, CA, January 2004. 92. C. I. Tomai and S.N. Srihari, Combination of Type III Digit Recognizers using Dempster-Shafer Theory of Evidence, Proceedings International Conference on Document Analysis Recognition (ICDAR), Edinburgh, Scotland, Aug. 2003. 93. S. N. Srihari, C. I. Tomai, B. Zhang and S-J. Lee, “Individuality of Numerals,” Proceedings International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland, August 2003. 94. B. Zhang and S. N. Srihari, “Individuality of Characters,” Proceedings International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland, August 2003. 95. B. Zhang and S. N. Srihari, “Individuality of Words,” Proceedings International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland, August 2003. 96. S.N.Srihari, C. Tomai, B. Zhang, S-J.Lee, Z. Shi and Y.C.Shin, “Handriwitng Matching and Recognition,” Proceedings Symposium of Document Image Undertanding (SDIUT), Greenbelt, MD, April 2003. 97. B. Zhang and S.N.Srihari, “Binary vector dissimilarity measures for handwriting identification,”Proceedings, Electronic Imaging, SPIE vol. 5010, January 2003, pp.28-38. 98. Lee, S., S.-H. Cha and S. N. Srihari, "Combining Macro and Micro Features for Writer Identification," SPIE, Document Recognition and Retrieval IX, San Jose, CA, January 2002, pp. 155-166. 99. Srihari, S. N., S.-H. Cha and S. Lee, "The Discriminatory Power of Handwriting," Invited Paper, SPIE, Document Recognition and Retrieval IX, San Jose, CA, January 2002, pp. 129-142. 100. Zhang, B., C. Tomai, A. Zhang and S. N. Srihari, "An Adaptive Image Retrieval System Using Wavelets," International Conference on Image Processing (ICIP 2002), Rochester, NY, September 2002. 101. Cha, S.-H., and S. N. Srihari, “Apriori Algorithm for Sub-category Classification Analysis of Handwriting,” Sixth International Conference on Document Analysis and Recognition (ICDAR'01), Seattle, WA, September 2001, pp. 1022-1025 102. Cha, S.-H., and S. N. Srihari, “Handwritten Document Image Database Construction and Retrieval Systems,” SPIE Document Recognition and Retrieval VIII, San Jose, CA, January, 2001, pp. 13-21. 103. Setlur, R., A. Lawson, V. Govindaraju and S. N. Srihari, “Truthing, Testing and Evaluation Issues in Complex Systems,” Sixth International Conference on Document Analysis and Recognition (ICDAR'01), Seattle, WA, September 2001, pp. 1205-1214. 104. Srihari, S. N., S.-H. Cha, H. Arora and S. Lee, “Individuality of Handwriting: A Validation Study,” Sixth International Conference on Document Analysis and Recognition (ICDAR'01), Seattle, WA, September 2001, pp. 106-109. 105. Srihari, S. N., S.-H. Cha and S. Lee, “Establishing Handwriting Individuality Using Pattern Recognition Techniques,”

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Sixth International Conf. Document Analysis and Recognition (ICDAR'01), Seattle, WA, Sept. 2001, pp. 1195-1204. 106. Cha, S.-H., Y.-C. Shin and S. N. Srihari, “Approximate String Matching for Stroke Direction and Pressure Sequences,” SPIE: Document Recognition and Retrieval VII, San Jose, CA, January 2000, pp. 2-10. 107. Cha, S.-H., and S. N. Srihari, “Assessing the Authorship Confidence of Handwritten Items,” Fifth Workshop on the Application of Computer Vision 2000, Palm Springs, CA, December 2000, pp. 42-47. 108. Cha, S.-H., and S. N. Srihari, “Comparing Color Images Using Angular Histogram Measures,” Joint Conference on Information Sciences, Atlantic City, NJ, February 2000, pp. 139-142. 109. Cha, S.-H., and S. N. Srihari, “Convex Hull Discriminant Function and Its Application to the Writer-Identification Problem,” Joint Conference on Information Sciences, Atlantic City, NJ, February 2000, pp. 13-16. 110. Cha, S.-H., and S. N. Srihari, “Distance between Histograms of Angular Measurements and its Application to Handwritten Character Similarity,” International Conference Pattern Recog., Barcelona, Spain, Sept. 2000, pp. 21-24. 111. Cha, S.-H., and S. N. Srihari, “Mapping the Many-Class Problem into a Dichotomy Using Distance Measures,” International Conference of Statistics, San Antonio, TX, March 2000, pp. 57-58. 112. Cha, S.-H., and S. N. Srihari, “Multiple Feature Integration for Writer Identification,” Seventh International Workshop on Frontiers of Handwriting Recognition, Amsterdam, The Netherlands, September 2000, pp. 333-342. 113. Cha, S.-H., and S. N. Srihari, “Nearest Neighbor Search Using Additive Binary Tree,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR00), Hilton Head, SC, June 2000, pp. 738-745. 114. Cha, S.-H., and S. N. Srihari, “System That Identifies Writers,” Seventeenth National Conference of American Association of Artificial Intelligence 2000, Austin, TX, July 2000, p. 1068. 115. Cha, S.-H., and S. N. Srihari, “Writer Identification: Statistical Analysis and Dichotomizer,” International Workshop on Structural and Syntactical Pattern Recognition 2000, Alicante, Spain, August 2000, pp. 123-132. 116. Srihari, S. N., “A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR,” Lecture Notes in Computer Science, IAPR International Workshop on Multiple Classifier Systems, Cagliari, Italy, June 2000, pp. 45-51. 117. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “Recognition of Strings Using Non-Stationary Markovian Models: An Application in ZIP Code Recognition,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR99), Fort Collins, CO, June 1999, pp. 174-179. 118. Cha, S.-H., Y.-C. Shin and S. N. Srihari, “Approximate Stroke Sequence String Matching Algorithm for Character Recognition and Analysis,” Fifth International Conference on Document Analysis and Recognition (ICDAR99), Bangalore, India, September 1999, pp. 53-56. 119. Govindaraju, V., S. N. Srihari and Y.-C. Shin, “Use of Handwriting Recognition Features in Handwriting Recognition,” International Graphonomics Society Conference, Singapore, June 1999, pp. 73-78. 120. Jung, M.-C., Y.-C. Shin and S.N. Srihari, “Machine-Printed Character Segmentation Method Using Side Profiles,” IEEE International Conference on Systems, Man and Cybernetics, Tokyo, Japan, October 1999. 121. Jung, M.-C., Y.-C. Shin and S. N. Srihari, “Multifont Classification Using Typological Attributes,” Fifth International Conference on Document Analysis and Recognition (ICDAR99), Bangalore, India, September 1999, pp. 353-356. 122. Mahadevan, U., and S. N. Srihari, “Parsing and Recognition of City, State, and ZIP Codes in Handwritten Addresses,” Fifth International Conf. Document Analysis Recognition (ICDAR99), Bangalore, India, Sept. 1999, pp. 325-328. 123. Park, J., V. Govindaraju and S. N. Srihari, “Efficient Word Segmentation Driven by Unconstrained Handwritten Phrase Recognition,” Fifth International Conference on Document Analysis and Word Recognition (ICDAR99), Bangalore, India, September 1999, pp. 605-608. 124. Srihari, S. N., “Mining Postal Databases for Address Interpretation,” International Symposium on Document Analysis and Speech Recognition, Indian Statistical Institute, Calcutta, India, December 1999. 125. Srihari, S. N., “A Task of Many Pattern Recognition Problems,” Second International Conference on Multimodal Interface (ICMI99), Kowloon Tong, Hong Kong, January 1999, pp. 2-4. 126. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Address Interpretation,” Mail Technology–Tomorrow’s World, Brighton, UK, June 1999, pp. 147-158. 127. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Information Theoretic Modeling of Postal Address Fields for Overcoming Ambiguity,” HKK Conference, Waterloo, Ontario, Canada, June 1999, pp. 105-110. 128. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Information Theoretic Analysis of Postal Address Fields for Automatic Address Interpretation,” Fifth International Conference on Document Analysis and Word Recognition (ICDAR99), Bangalore, India, September 1999, pp. 309-312. 129. Wang, X., V. Govindaraju and S. N. Srihari, “Multi-Experts for Touching Digit String Recognition,” Fifth International Conference on Document Analysis and Word Recognition (ICDAR99), Bangalore, India, September 1999, pp. 800-803. 130. Bartnik, D., V. Govindaraju, S. N. Srihari and B. Phan, “Postal Reply-Card Mail Processing,” Fourteenth International Conference on Pattern Recognition, Brisbane, Australia, August 1998, pp. 633-636. 131. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “A Methodology for Deriving Probabilistic Correctness from

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Recognizers,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR98), Santa Barbara, CA, June 1998, pp. 930-935. 132. Govindaraju, V., K. Ianakiev and S. N. Srihari, “Improving Classifier Accuracy by Simulating Fuzzy Boundaries between Classes,” North American Fuzzy Logic and Image Processing Conf., Pensacola, FL, August 1998, pp. 161-164. 133. Kim, G., V. Govindaraju and S. N. Srihari, “Architecture for Handwritten Text Recognition Systems,” Sixth International Workshop on Frontiers of Handwriting Recognition (IWFHRVI), Taejon, Korea, Aug. 1998, pp. 113-122. 134. Madhvanath, S., and V. Govindaraju, “Perceptual Features for Off-Line Handwritten Word Recognition: A Framework for Heuristic Prediction,” IAPR Workshop Matching and Representation, Syntactic and Statistical Pattern Recognition, Sydney, Australia, August 1998. 135. Park, J., V. Govindaraju, and S. N. Srihari, “OCR in Hierarchical and Multi-Resolution Feature Space,” IEEE Conference on Systems, Man and Cybernetics, San Diego, CA, October 1998, pp. 4324-4329. 136. Srihari, S. N., W.-J. Yang, V. Govindaraju, X. Song and X. Wang, “Statistical Analysis of United States Postal Addresses,” International Conference on Combinatorics, Statistics, Pattern Recognition and Related Areas (Fifth International Conference of the Forum for Interdisciplinary Mathematics), Mysore, India, December 1998, pp. 71-72. 137. Wang, X., V. Govindaraju and S. N. Srihari, “Holistic Recognition of Touching Digits,” Sixth International Workshop on Frontiers of Handwriting Recognition (IWFHRVI), Taejon, Korea, August 1998, pp. 295-303. 138. Bouchaffra, D., E. Koontz, V. Krpsundar, R. K. Srihari and S. N. Srihari, “Integrating Signal and Language Context to Improve Handwritten Phrase Recognition: Alternative Approaches,” Sixth International Workshop on Artificial Intelligence and Statistics, Fort Lauderdale, FL, January 1997, pp. 47-54. 139. Govindaraju, V., and S. N. Srihari, “Paradigms in Handwriting Recognition,” IEEE International Conference on Systems, Man and Cybernetics, Orlando, FL, October 1997, pp. 1498-1503. 140. Hong, T. and S. N. Srihari, “Representing OCR'ed Documents in HTML,” International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'97), Gold Coast, Australia, February 1997, pp. 18-22. 141. Hong, T. and S. N. Srihari, “Representing OCR'ed Documents in HTML,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 831-835. 142. Madhvanath, S., E. Kleinberg, V. Govindaraju and S. N. Srihari, “The HOVER System for Rapid Holistic Verification of Off-line Handwritten Phrases,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 855-859. 143. Niyogi, D., and S. N. Srihari, “The Use of Document Structure Analysis to Retrieve Information from Documents in Digital Libraries,” SPIE/IS&T Symposium on Electronic Imaging: Science & Technology, San Jose, CA, February 1997. 144. Shi, Z., S. N. Srihari, Y.-C. Shin and V. Ramanaprasad, “A System for Segmentation and Recognition of Totally Unconstrained Handwritten Numeral Strings,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 455-458. 145. Srihari, S. N., and E. J. Keubert, “Integration of Handwritten Address Interpretation Technology into the United States Postal Service Remote Computer Reader System,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 892-896. 146. Srihari, S. N., and G. Kim, “PENMAN: A System for Reading Unconstrained Handwritten Page Images,” Symposium on Document Image Understanding Technology (SDIUT97), Annapolis, MD, April 1997, pp. 142-153. 147. Favata, J., S. N. Srihari and V. Govindaraju, “Off-Line Handwritten Sentence Recognition,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 171-176. 148. Govindaraju, V., and S. N. Srihari, “Assessment of Image Quality to Predict Readability of Documents,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, pp. 137-138. 149. Hong, T., and J. J. Hull and S. N. Srihari, “A Unified Approach towards Text Recognition,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p. 130. 150. Hong, T., G. Srikantan, V.C. Zandy, C. Fang and S.N. Srihari, Character Recognition in a Japanese Text Recognition System, IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p.p. 51-62. 151. Hong, T., S. Wu, S. N. Srihari, “Evaluating Japanese Document Recognition in the Internet/Intranet Environment,” Fifth Symposium on Document Analysis and Information Retrieval (SDAIR96), Las Vegas, NV, April 1996, pp. 271- 286. 152. Hong, T., S. Wu and S. N. Srihari, “Evaluating Japanese Document Recognition in the Internet/Intranet Environment,” Workshop on Document Analysis Systems (DAS96), October 1996, pp. 633-650. 153. Kim, G., V. Govindaraju and S. N. Srihari, “Extension of a Handwritten Word Recognition Method to Street Name Images,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 221-226. 154. Kim, G., V. Govindaraju and S. N. Srihari, “Handwritten Word Recognition Using Dynamic Matching with Variable Duration,” International Conference on Acoustics, Speech and Signal Processing, Atlanta, GA, May 1996, pp. 3454-

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3457. 155. Kim, G., V. Govindaraju and S. N. Srihari, “A Segmentation and Recognition Strategy for Handwritten Phrases,” Thirteenth International Conference on Pattern Recognition (ICPR96), Vienna, Austria, August 1996, pp. D510-D513. 156. Madhvanath, S., and S. N. Srihari, “Effective Reduction of Large Lexicons for Recognition of Off-Line Cursive Script,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp.189-194. 157. Madhvanath, S., and S. N. Srihari, “Modes and Measures: A Framework for Design of Parallel Word Classifier Combination Schemes,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 449-452. 158. Madhvanath, S., and S. N. Srihari, “A Technique for Local Baseline Determination,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 445-448. 159. Mahadevan, U., and S. N. Srihari, “Hypothesis Generation for Word Separation in Handwritten Lines,” Fifth International Workshop Frontiers Handwriting Recognition (IWFHRV), Essex, England, Sept.1996, pp. 453-456. 160. Niyogi, D., and S. N. Srihari, “Using Domain Knowledge to Derive the Logical Structure of Documents,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p. 133. 161. Ramanaprasad, V., Y.-C. Shin and S. N. Srihari, “Reading Handprint Addresses on IRS Tax Forms,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, pp. 135-136. 162. Sheikholeslami, G., S. N. Srihariand and V. Govindaraju, “Computer-Aided Graphology,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 457-460. 163. Srihari, S. N., “Image Quality and Readability,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January, 1996. 164. Srihari, S. N., “Recent Advances in Off-line Handwriting Recognition,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 1-15. 165. Srihari, S. N., “System for Reading Handwritten Documents,” IEEE International Conference on Systems, Man, and Cybernetics, San Jose, CA, January 1996. 166. Srihari, S. N., G. Srikantan and T. Hong, “A General-Purpose Japanese OCR System,” Fifth Symposium on Document Analysis and Information Retrieval (SDAIR96), Las Vegas, NV, April 1996, pp. 271-286. 167. Srikantan, G., T. Hong, V. C. Zandy and S. N. Srihari, “Japanese OCR System for Machine-Printed Document Images,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p. 131. 168. Bhate, A., S. W. Lam and S. N. Srihari, “Sliding Window Technique for Word Recognition,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, February 1995, p. 236. 169. Govindaraju, V., and S.N. Srihari, “Image Quality and Human Readability,” IEEE International Conference on Image Processing (ICIP95), Washington, D.C., October 1995, Vol. III, pp. 324-327. 170. Hong, T., S.W. Lam, J.J. Hull and S.N. Srihari, “The Design of a Nearest-Neighbor Classifier and Its Use for Japanese Character Recognition,” Third International Conference on Document Analysis and Recognition (ICDAR'95), Montreal, Canada, August 1995, pp. 270-273. 171. Hong, T., S. W. Lam, J. J. Hull and S. N. Srihari, “Visual Similarity Analysis of Chinese Characters and Its Uses in Japanese OCR,” IS&T/SPIE Symposium Electronic Imaging: Science Tech., San Jose, California, Feb. 1995, p. 242. 172. Lam, S. W., Q. Liao and S. N. Srihari, “Divide-and-Conquer Approach to Japanese Text Segmentation,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, California, February 1995, p. 241. 173. Lee, D.-S., and S. N. Srihari, “Classifier Combination Using Neural Network Approach,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, California, February 1995, p. 236. 174. Lee, D.-S., and S.N. Srihari, “A Theory of Classifier Combination: The Neural Network Approach,” Third International Conference on Document Analysis Recognition (ICDAR'95), Montreal, Canada, August 1995, pp. 42-45. 175. Lii, J., and S. N. Srihari, “Location of Name and Address on Fax Cover Pages,” Third International Conference on Document Analysis and Recognition (ICDAR'95), Montreal, Canada, August 1995, pp. 756-759. 176. Madhvanath, S., V. Govindaraju, V. Ramanaprasad, D.-S. Lee and S. N. Srihari, “Reading Handwritten US Census Forms,” Third Int. Conference Document Analysis Recognition (ICDAR'95), Montreal, Canada, Aug. 1995, pp. 82-85. 177. Niyogi, D., and S.N. Srihari, “Knowledge-Based Derivation of Document Logical Structure,” Third International Conference on Document Analysis and Recognition (ICDAR '95), Montreal, Canada, August 1995, pp. 472-475. 178. Srihari, S. N., “Japanese OCR ,” Symp. Doc. Image Und. Tech. (SDIUT), Bowie, MD, Oct. 1995, pp. 236-246. 179. Srihari, S. N., “System for Reading Handwritten Documents,” IEEE International Conference on Systems, Man and Cybernetics, Vancouver, Canada, October 1995. 180. Srihari, S. N., V. Govindaraju and J. Favata, “Unconstrained Handwritten Text Recognition,” Symposium on Document Image Understanding Technology (SDIUT), Bowie, MD, October 1995, pp. 226-235. 181. Srihari, S. N., Y.-C. Shin, V. Ramanaprasad and D.-S. Lee, “Name and Address Block Reader System for Tax Form Processing,” Third Int. Conf. Document Analysis Recog. (ICDAR ’95), Montreal, Canada, Aug. 1995, pp. 5-10.

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182. Srikantan, G., and S. N. Srihari, “Data Representations in Learning,” Fifth Int. Workshop on Artificial Intelligence & Statistics, Florida, January 1995, 495. 183. Zhao, S., and S. N. Srihari, “A Word Recognition Algorithm for Machine-Printed Word Images of Multiple Fonts and Varying Qualities,” Third Int. Conf. Document Anal. Recog. (ICDAR'95), Montreal, Canada, Aug.1995, pp. 351-354. 184. Zhao, X., and S. N. Srihari, “Word Recognition Using a Lexicon Constrained by First/Last Character Decisions,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, California, February 1995, p. 238. 185. Cullen, P., R. S. Curtis, P. D. Filipski, J. J. Hull and S. N. Srihari, “Machine Print Address Interpretation Utilizing Contextual Knowledge,” Inst. Mech. Engineers Mail Systems 2000 Int. Conf., London, England, May 1994, pp. 97-105. 186. Favata, J., G. Srikantan and S. N. Srihari, “Hand-printed Character/Digit Recognition Using a Multiple Feature/Resolution Philosophy,” Int. Wkshp Front. Hand. Recog. (IWFHR IV), Dec. 1994, Taipei, Taiwan, pp. 57-66. 187. Govindaraju, V., R. K. Srihari and S. N. Srihari, “Handwritten Text Recognition,” International Conference on Document Analysis Systems (DAS 94), Kaiserslautern, Germany, October 1994, pp. 157-171. 188. Lam, S., V. Govindaraju, R. K. Srihari, J. J. Hull and S. N. Srihari, “Intelligent Data Retrieval from Raster Images of Documents,” First Annual Conference Theory Practice of Digital Libraries, College Station, TX, Jun. 1994, pp. 34-40. 189. Lii, J., and S. N. Srihari, “Use of Character Recognition and Syntax in Locating Address Paragraphs in Complex Documents,” Twelfth International Conference on Pattern Recognition, October 1994, pp. 1241-1255. 190. Srihari, S. N., S. Lam and J. J. Hull, “Document Recognition for Digital Libraries,” Workshop on Digital Libraries, Newark, NJ, May 1994. 191. Srihari, S. N., R. K. Srihari and V. Govindaraju, “Handwritten Text Recognition,” Fourth International Workshop on the Frontiers of Handwriting Recognition (IWFHRIV), Taipei, Taiwan, December 1994, pp. 265-274. 192. Srikantan, G., R. K. Fenrich and S. N. Srihari, “Contrast Enhancement for Mailpiece Images,” IEEE Southwest Symposium on Image Analysis and Interpretation, Dallas, TX, April 1994, p. 82. 193. Srikantan, G., and S. N. Srihari, “A Study Relating Image Sampling Rate and Image Pattern Recognition,” IEEE Conference on Computer Vision and Pattern Recognition, Seattle, WA, June 1994, p. 709. 194. Lam, S.W., L. Javanbakht and S.N. Srihari, “Anatomy of a Form Reader,” Second International Conference on Document Analysis and Recognition (ICDAR93), Tsukuba Science City, Japan, October 1993, pp. 506-509. 195. Lam, S.W., X. Shen and S.N. Srihari, “Representing Lexicons by Modified Tie for Fast Partial String Matching,” SPIE/IS&T Symposium on Electronic Imaging Science and Technology, San Jose, CA, February 1993. 196. Lii, J., P.W. Palumbo and S.N. Srihari, “Address Block Location Using Character Recognition and Address Syntax,” Second International Conference Document Anal. Recognition (ICDAR93), Tsukuba, Japan, Oct. 1993, pp. 330-335. 197. Liu, Y., R. Fenrich and S.N. Srihari, “An Object Attribute Thresholding Algorithm for Document Image Binarization,” Second International Conf. Document Analysis Recog. (ICDAR93), Tsukuba, Japan, Oct. 1993, pp. 278-281. 198. Srihari, S. N., “From Pixels to Paragraphs: The Use of Models in Text Recognition,” Second Symposium on Document Analysis and Recognition, Las Vegas, NV, April 1993, 47-64. 199. Srihari, S.N., V. Govindaraju and A. Shekhawat, “Interpreting Handwritten Addresses in US Mailstream,” Second International Conference on Document Analysis and Recognition (ICDAR93), Tsukuba, Japan, Oct. 1993, pp. 291-294. 200. Srikantan, G., S.W. Lam and S.N. Srihari, “Gradient-Based Contour Encoding for Grayscale Character Recognition,” SPIE/IS&T Symposium on Electronic Imaging Science and Technology, San Jose, CA, February 1993. 201. Zhou, J., V. Govindaraju, R. Acharya and S.N. Srihari, “Recognition of State Name Abbreviations,” Third International Workshop on Frontiers of Handwriting Recognition (IWFHRIII), Buffalo, NY, May 1993, pp. 423-430. 202. Chen, M. Y., A. Kundu, J. Zhou and S. N. Srihari, “Off-line Handwritten Word Recognition Using Hidden Markov Model,” United States Postal Service Advanced Technology Conf., Washington, DC, November 1992, pp. 563-578. 203. Cullen, P., T.-K. Ho, J. J. Hull, M. Prussak and S .N. Srihari, “Contextual Analysis of Machine-Printed Addresses,” Machine Vision Applications Character Recognition Industrial Inspection, San Jose, CA, February 1992, pp. 257-268. 204. Cullen, P., J. J. Hull and S. N. Srihari, “A Constraint-based Approach to Postal Address Interpretation,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 367-377. 205. Favata, J., and S. N. Srihari, “Recognition of General Handwritten Words Using a Hypothesis Generation and Reduction Methodology,” United States Postal Service Adv. Tech. Conf, Washington, DC, Nov. 1992, pp. 237-251. 206. Fenrich, R., S. N. Srihari, P. Scott and M. Woolston, “Real-time High-resolution Image Acquisition Prototype,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 1113-1127. 207. Filipski, P., J. J. Hull and S. N. Srihari, “Compression for Fast Read-only Access of a Large Database,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 795-807. 208. Govindaraju, V., S. N. Srihari and D. Sher, “A Computational Model for Face Location Based on Cognitive Principles,” AAAI Tenth National Conference on Artificial Intelligence, San Diego, CA, July 1992, pp. 350-355. 209. Govindaraju, V., D. Wang and S. N. Srihari, “Using Temporal Information in Off-line Word Recognition,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 529-544. 210. Ho, T. K., J. J. Hull and S. N. Srihari, “On Multiple Classifier Systems for Pattern Recognition,” Eleventh Annual

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International Conference on Pattern Recognition, Amsterdam, Netherlands, 1992, pp. 84-87. 211. Lam, S., A. Girardin and S. N. Srihari, “Gray Scale Character Recognition Using Boundary Features,” Machine Vision Applications in Character Recognition and Industrial Inspection, San Jose, CA, February 1992, pp. 98-105. 212. Lee, D. S., and S. N. Srihari, “Machine-printed Character Recognition with Biological and Theoretical Bases,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 689-699. 213. Li, L., T. K. Ho, J. J. Hull and S. N. Srihari, “A Hypothesis Testing Approach to Word Recognition Using Dynamic Feature Selection,” Eleventh Annual Int. Conf. Pattern Recognition, Amsterdam, Netherlands, 1992, pp. 586-589. 214. Lii, Y., P. W. Palumbo and S. N. Srihari, “Use of Character Recognition and Address Syntax in Address Block Location,” United States Postal Service Advanced Technology Conference, Wash. DC, Nov. 1992, pp. 1241-1255. 215. Srihari, S. N., “Model-based OCR,” DARPA Workshop Document Understanding, May 1992, Palo Alto, CA, 5 pages. 216. Srihari, S.N., “Next Generation USPS Address Recognition Unit,” Japanese Postal Technology Conference, Tokyo, Japan, January 1992, 8 pages. 217. Srihari, S. N., E. Cohen, V. Govindaraju and A. Shekhawat, “Determining Delivery Point Codes on Handwritten Addresses,” United States Postal Service Advanced Technology Conf., Wash. DC, November 1992, pp. 321-335. 218. Wong, P. K., T. K. Ho and S. N. Srihari, “Firm Recognition for Automatic Address Interpretation,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 757-770. 219. Cohen, E., J. J. Hull and S. N. Srihari, “Understanding Spatially Structured Handwritten Text,” International Conference on Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 984-992 220. Govindaraju, V., and S. N. Srihari, “Separating Handwritten Text from Overlapping Non-textual Contours,” Second International Workshop Frontiers Handwriting Recognition (IWFHRII), Bonas, France, September 1991, pp. 229-240. 221. Ho, T. K., J. J. Hull and S. N. Srihari, “Word Recognition with Multi-level Contextual Knowledge,” First International Conference on Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 905-916. 222. Hull, J. J., T. K. Ho, J. Favata, V. Govindaraju and S. N. Srihari, “Combination of Segmentation-based and Holistic Handwritten Word Recognition Algorithms,” Int. W. Front. H. Recog. (IWFHRII), Bonas, Fr., Sept.1991, pp. 111-122. 223. Lam, S., and S. N. Srihari, “Frame-Based Knowledge Representation for Multi-Domain Document Layout Analysis,” IEEE Conference on Systems, Man and Cybernetics, Charlottesville, VA, September 1991. 224. Lam, S., and S. N. Srihari, “Multi-domain Document Layout Understanding,” First International Conference on Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 112-120. 225. Wang, D., and S. N. Srihari, “Analysis of Form Images,” First International Conference on Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 181-191. 226. Cohen, E., J. J. Hull and S. N. Srihari, “Reading and Understanding Handwritten Addresses,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 821-836. 227. Cullen, P. B., T. K. Ho, J. J. Hull, M. Prussak and S. N. Srihari, “Contextual Analysis of Machine-printed Addresses,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 779-793. 228. Demjanenko, V., Y. C. Shin, R. Sridhar, P. W. Palumbo and S. N. Srihari, “Real-time Connected Component Analysis for Address Block Location,” United States Postal Service Adv. Tech. Conf., Wash. DC, Nov. 1990, pp. 1059-1066. 229. Favata, J. T., and S .N. Srihari, “Recognition of Handwritten Words for Address Reading,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 191-205. 230. Govindaraju, V., S. N. Srihari and D. B. Sher, “A Computational Model for Face Location,” Third International Conference Computer Vision, Osaka, Japan, December 1990, pp. 718-721. 231. Ho, T. K., J. J. Hull and S. N. Srihari, “Combination of Structural Classifiers,” Workshop on Structural and Syntactic Pattern Recognition, Murray Hill, NJ, June 1990, pp. 123-136. 232. Ho, T. K., J. J. Hull and S. N. Srihari, “A Word Shape Analysis Approach to Recognition of Degraded Word Images,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 217-229. 233. Lam, S., D. Wang and S. N. Srihari, “Reading Newspaper Text,” Tenth International Conference on Pattern Recognition, Atlantic City, NJ, June 1990, pp. 703-705. 234. Lee, D. S., S. Lam and S. N. Srihari, “A Structural Approach to Recognize Hand-printed and Degraded Machine- printed Characters,” Workshop on Structural & Syntactic Pattern Recognition, Murray Hill, NJ, June 1990, pp. 256- 272. 235. Palumbo, P. W., J. Soh and S. N. Srihari, “Real-time Address Block Location Using Pipelining and Multiprocessing,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 73-87. 236. Srihari, S. N., “High-performance Reading Machines,” Vision Interface '90, Halifax, Nova Scotia, Canada, May 1990, pp. 150-155. 237. Srihari, S. N., “High-performance Reading Machines,” Conference on Knowledge-Based Computer Systems, Pune, India, December 1990, pp. 489-492. 238. Srihari, S. N., “Reading Unconstrained Handwriting with Bounded Context,” International Workshop on Frontiers of Handwriting Recognition, Montreal, Canada, April 1990, pp. 109-116.

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239. Chen, J. S., and S. N. Srihari, “Candidate Ordering and Elimination in Model-based Fault Diagnosis,” Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI, August 1989, pp. 1363-1368. 240. Govindaraju, V., S. Lam, D. Niyogi, D. B. Sher, R. K. Srihari, S. N. Srihari and D. Wang, “Newspaper Image Understanding,” Conference on Knowledge-Based Computer Systems, Bombay, India, December 1989, pp. 375-386. 241. Govindaraju, V., D. B. Sher, R. K. Srihari and S. N. Srihari, “Locating Human Faces in Newspaper Photographs,” IEEE-CS Conference on Computer Vision Pattern Recognition, San Diego, CA, June 1989, pp. 549-555. 242. Soh, J., P. W. Palumbo and S. N. Srihari, “Real Time Recognition of Address Blocks on Mail Pieces,” Optical Society of America Topical Meeting: Image Understanding and Machine Vision, Cape Cod, MA, June 1989, pp. 10-13. 243. Srihari, S. N., “Feature Extraction for Address Block Location,” From Pixels to Features: COST-13 Workshop, Bonas, France, 1989, pp. 261-274. 244. Hull, J. J., S. N. Srihari, E. Cohen and C. L. Kuan, “A Blackboard-Based Approach to Handwritten ZIP Code Recognition,” United States Postal Service Advanced Technology Conference, Washington DC, May 1988, pp. 1018- 1032. 245. Hull, J. J., S. N. Srihari, E. Cohen, L. Kuan, P. Cullen and P. W. Palumbo, “A Blackboard-Based Approach to Handwritten ZIP Code Recognition,” Ninth International Conference on Pattern Recognition, Rome, Italy, November 1988, pp. 111-113. 246. Kuan, L., and S. N. Srihari, “A Stroke-Based Approach to Handwritten Numeral Recognition,” United States Postal Service Advanced Technology Conference, May 1988, pp. 1033-1041. 247. Niyogi, D., and S. N. Srihari, “Expert Systems and Pattern Recognition,” Seventh Biennial Convention of South East Asia Regional Computer Confederation, November 1988, pp. 119-128. 248. Palumbo, P. W., and S. N. Srihari, “Advanced Computer Architectures for Address Block Location,” United States Postal Service Advanced Technology Conference, Washington DC, May 1988, pp. 318-326. 249. Pawlicki, T. F., D.-S. Lee, J. J. Hull and S. N. Srihari, “Neural Network Models and Their Application to Handwritten Digit Recognition,” IEEE International Conference on Neural Networks, San Diego, CA, July 1988, pp. 63-70 250. Pawlicki, T. F., D.-S. Lee, J. J. Hull and S. N. Srihari, “Neural Network Models and Their Application to Handwritten Digit Recognition,” United States Postal Service Advanced Technology Conference, Washington, DC, May 1988, pp. 751-767. 251. Wang, C.-H., P. W. Palumbo and S. N. Srihari, A Framework for Object Recognition and Its Application to Locating Address Blocks on Mail Pieces,” AAAI Blackboard Workshop, St. Paul, MN, August 1988. 252. Wang, C.-H., P. W. Palumbo and S. N. Srihari, “Object Recognition in Visually Complex Environments: Architecture for ABLS,” Ninth International Conference on Pattern Recognition, Rome, Italy, November 1988, pp. 365-367. 253. Wang, C.-H., P. W. Palumbo and S. N. Srihari, “Performance Evaluation of a System to Recognize Address Blocks on Mail Pieces,” AAAI Seventh National Conference on Artificial Intelligence, Minneapolis, MN, August 1988, pp. 837- 841. 254. Wang, C.-H., P. W. Palumbo, S. M. Tylock, J. J. Hull and S. N. Srihari, “Performance of a System to Locate address Blocks on Mail Pieces,” United States Postal Service Advanced Technology Conference, Washington, DC, May 1988, pp. 705-718. 255. Geller, J., M.-R Taie, S. C. Shapiro and S. N. Srihari, “Device Representation and Graphics Interfaces of VMES,” Application of AI in Engineering, Cambridge, MA, August 1987, pp. 15-28. 256. Hull, J. J., and S. N. Srihari, “Knowledge Utilization in Handwritten ZIP-Code Recognition,” Tenth International Joint Conference on Artificial Intelligence, Milan, Italy, August 1987, pp. 848-850. 257. Niyogi, D., and S. N. Srihari, “Using a Blackboard Architecture for Control in a Knowledge-based Document Understanding System,” SPIE: Applications of Artificial Intelligence, Orlando, FL, 1987, pp. 319-326. 258. Srihari, S.N., “Document Image Analysis: An Overview,” SPSE’s 40th Annual Conference and Symposium on Hybrid Imaging Systems, Rochester, May 1987, pp. 28-31. 259. Srihari, S. N., and R. Bozinovic, “A Multi-level Perception Approach to Reading Cursive Script,” Tenth International Joint Conference on Artificial Intelligence, Milan, Italy, August 1987, pp. 844-847. 260. Taie, M.-R., and S. N. Srihari, “Modeling Connections for Circuit Diagnosis,” Third Conference on Artificial Intelligence Applications, Orlando, FL, February 1987, pp. 81-86. 261. Hull, J. J., and S. N. Srihari, “A Computational Approach to Shape Recognition: Hypothesis Generation and Testing,” IEEE-CS Conference on Computer Vision Pattern Recognition, Miami Beach, FL, June 1986, pp. 156-161. 262. Hull, J. J., and S. N. Srihari, “Use of External Information in ZIP-Code Recognition,” United States Postal Service Advanced Technology Conference, Washington, DC, October 1986, pp. 361-370. 263. Niyogi, D., and S. N. Srihari, “A Knowledge-Based System for Document Image Understanding,” Second Expert Systems in Government Symposium, McLean, VA, October 1986, pp. 128-134. 264. Niyogi, D., and S. N. Srihari, “A Rule-Based System for Document Understanding,” AAAI Fifth National Conference on Artificial Intelligence, Philadelphia, PA, August 1986, pp. 789-793.

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265. Palumbo, P. W., and S. N. Srihari, “Text Parsing Using Spatial Information for Recognizing Addresses in Mail Pieces,” Eighth International Conference on Pattern Recognition, Paris, France, October 1986, pp. 1068-1070. 266. Palumbo, P. W., P. Swaminathan and S. N. Srihari, “Document Image Binarization: Comparison of Techniques,” SPIE Applications of Digital Image Processing IX, San Diego, August 1986, pp. 278-285. 267. Shapiro, S. C., S. N. Srihari, M-R. Taie and J. Geller, “VMES: A Network-Based Versatile Maintenance Expert System,” Applications of AI to Engineering, Southampton, England, April 1986, pp. 925-936. 268. Srihari, S. N., “Document Image Understanding,” ACM-IEEE C/S Fall Joint Computer Conference, Dallas, TX, November 1986, pp. 87-96. 269. Srihari, S. N., J. J. Hull, P. W. Palumbo and C.-H. Wang, “Address Block Location: Specialized Tools and Problem- Solving Architecture,” United States Postal Service Advanced Technical Conference, Washington, DC, October 1986, pp. 116-131. 270. Srihari, S. N., and C.-H. Wang, “A Blackboard Architecture for Object Recognition,” SPIE Proceedings: Automated Inspection and Measurement, Cambridge, MA, October 1986, pp. 224-232. 271. Srihari, S. N., and G. W. Zack, “Document Image Analysis,” Eighth International Conference on Pattern Recognition, Paris, France, October 1986, pp. 434-436. 272. Taie, M. R., and S. N. Srihari, “Device Modeling for Fault Diagnosis,” Second Expert Systems in Government Symposium, McLean, VA, October 1986, pp. 144-150. 273. Taie, M. R., S. N. Srihari, J. Geller and S. C. Shapiro, “Device Representation Using Instantiation Rules and Structural Templates,” Canadian Artificial Intelligence Conference, Montreal, May 1986, pp. 124-128. 274. Wang, C.-H., and S. N. Srihari, “Object Recognition in Structured and Random Environments: Locating Address Blocks in Mail Piece Images,” AAAI Fifth National Artificial Intelligence Conference, Philadelphia, PA, August 1986, pp. 1133-1137. 275. Xiang, Z., and S. N. Srihari, “Diagnosis Based on Empirical and Model Knowledge,” Sixth International Workshop Expert Systems, Avignon, France, April 1986, pp. 835-848. (Received award for “Outstanding Communication.”) 276. Xiang, Z., and S. N. Srihari, “Diagnosis Using Multi-level Reasoning,” Second Expert Systems in Government Symposium, McLean, VA, October 1986, pp. 151-158. 277. Kumar, R., and S. N. Srihari, “An Expert System for the Interpretation of Cranial CT Scan Images,” Expert Systems in Government Symposium, McLean, VA, October 1985, pp. 548-557. 278. Xiang, Z., J. G. Chutkow, S. C. Shapiro and S. N. Srihari, “Representation of Spatial Structure and Function in Diagnosis,” Second Conference on Artificial Intelligence Applications, Miami Beach, FL, December 1985, pp. 223-228. 279. Xiang, Z., and S. N. Srihari, “Graphics Interfaces to a Neurological Diagnosis System,” National Computer Graphics Association Conference, Dallas, TX, April 1985, pp. 215-222. 280. Xiang, Z., and S. N. Srihari, “Spatial Structure and Function Representation in Diagnostic Expert Systems,” Fifth International Workshop on Expert Systems, Avignon, France, May 1985, pp. 191-206. 281. Xiang, X., S. N. Srihari, S. C. Shapiro and J. G. Chutkow, “A Modeling Scheme for Diagnosis,” Expert Systems in Government Symposium, McLean, VA, October 1985, pp. 538-547. 282. Bozinovic, R., and S. N. Srihari, “Knowledge-based Cursive Script Interpretation,” Seventh International Conference on Pattern Recognition, Montreal, Canada, August 1984, pp. 774-777. 283. Hardas, D., and S. N. Srihari, “An Architecture for Progressive Refinement of Grey-level 3-D Images,” Seventh International Conference on Pattern Recognition, Montreal, Canada, August 1984, pp. 224-226. 284. Xiang, Z., and S. N. Srihari, “Representation of Structure in Neurological Diagnosis,” International Conference Computers, Systems & Signal Processing, Bangalore, India, December 1984, pp. 1166-1169. 285. Xiang, Z., S. N. Srihari, S. C. Shapiro and J. G. Chutkow, “Analogical and Propositional Representations of Structure in Neurological Diagnosis,” First Conference on Artificial Intelligence Applications, Denver, CO, December 1984, pp. 127-132. 286. Bozinovic, R., and S. N. Srihari, “Use of Knowledge in Visual Interpretation of Cursive Script,” IEEE-SMC International Conference on Cybernetics and Society, Bombay, India, 1983, pp. 187-191. 287. Srisuresh, P., and S. N. Srihari, “A Shrinking Algorithm for 3-D Objects,” IEEE-CS Conference on Computer Vision and Pattern Recognition, Arlington, VA, 1983, pp. 392-393. 288. Bozinovic, R., and S. N. Srihari, “A String Correction Algorithm for Cursive Script Recognition,” Sixth International Conference on Pattern Recognition, Munich, West Germany, 1982, pp. 44-46. 289. Hull, J. J., and S. N. Srihari, “Comparison of Two Contextual Postprocessing Algorithms for Text Recognition,” IEEE- CS Conference Pattern Recognition and Image Processing, Las Vegas, NV, June 1982, pp. 146-151. 290. Srihari, S. N., “Hierarchical Data Structures and Progressive Refinement of 3-D Images,” IEEE-CS Conference on Pattern Recognition Image Processing, Las Vegas, NV, June 1982, pp. 485-490. 291. Srihari, S. N., and J. J. Hull, “Knowledge Integration in Text Recognition,” AAAI National Conference on Artificial Intelligence, Pittsburgh, PA, August 1982, pp. 148-151.

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292. Srihari, S. N., J. J. Hull and R. Choudhari, “Integration of Top-down and Bottom-up Knowledge in Text Error Correction,” AFIPS National Computer Conference, Houston, TX, June 1982, pp. 501-508. 293. Srihari, S.N., J.J. Hull and R. Choudhari, “An Algorithm for Integrating Diverse Knowledge Sources in Text Recognition,” ACM Conference on Office Information Systems, Philadelphia, PA, 1982, pp. 46-54. 294. Srihari, S. N., and J. Tindall, “Multiresolution Representation of Three-dimensional Objects,” IEEE-SMC International Conference Cybernetics and Society, Seattle, WA, October 1982, pp. 327-331. 295. Yau, M., and S. N. Srihari, “Convex Hulls from Hierarchical Data Structures,” Seventh Conference Canadian Man- Computer Communications Society, Waterloo, Ontario, June 1981, pp. 163-171. 296. Yau, M., and S. N. Srihari, “Recursive Generation of Hierarchical Data Structures for Multidimensional Digital Images,” IEEE-CS Conference Pattern Recognition and Image Processing, Dallas, TX, August 1981, pp. 42-44. 297. Srihari, S. N., “On the Complexity of Determining Equivalence of Decision Algorithms,” International Conference Cybernetics and Society, Cambridge, MA, October 1980, pp. 553-556. 298. S. N. Srihari, “Hierarchical Representations for Serial Section Images,” Fifth International Conference on Pattern Recognition, Miami Beach, FL, December 1980, pp. 1075-1080. 299. Srihari, S. N., “Pattern Classification with Composite Classes,” IEEE-CS Conference on Pattern Recognition and Image Processing, Chicago, IL, August 1979, pp. 173-180. 300. Srihari, S. N., T. Snabb and L. J. White, “An Algorithm for Determining Identity of Nearest-neighbor and Potential Function Decision Rules,” IEEE-CS Conference on Pattern Recognition and Image Processing, Chicago, IL, August 1979, pp. 63-70. 301. Srihari, S. N., J. K. Udupa and M. Yau, “Understanding the Bin-of-Parts,” International Conference on Cybernetics and Society, Denver, CO, October 1979, pp. 44-49.

9.5 United States Patents

1. Srihari, S. N., Y. C. Shin, et.al., Method and Apparatus for Analyzing and/or Comparing Handwritten and/or Biometric Samples, United States Patent No. 7,580,551, Aug 29, 2009. 2. Shin, Y.-C., R. Sridhar, S. Srihari and V. Demjanenko, Local Adaptive Contrast Enhancement, United States Patent No. 5,524,070, June 4, 1996. 3. Govindaraju, V., D. Wang and S. N. Srihari, System for recognizing handwritten words of cursive script, United States Patent No. 5,515,455, May 7, 1996. 4. Fenrich, R. K., and S. N. Srihari, A system for recognizing handwritten character strings containing overlapping and/or broken characters, United States Patent Number 5,321,768, June 14, 1994. 5. Shin, Y.-C., R. Sridhar, V. Demjanenko, P. W. Palumbo and S. N. Srihari, Digital Data Memory Unit and Memory Unit Array, United States Patent Number 5,257,220, October 26, 1993. 6. Kuan, L., J. J. Hull and S. N. Srihari, Method and apparatus for handwritten character recognition, United States Patent Number 5,058,182, Oct. 15, 1991. 7. Srihari, S. N., and J. J. Hull, A system to achieve automatic recognition of linguistic strings, United States Patent Number 4,654,875, March 31, 1987.

9.6 Abridged Papers/Abstracts

1. Srihari, S.N., “Quantitative Assessment of Handwriting,” European Academy of Forensic Sciences Meeting, September 2003, p.59. 2. Srihari, S. N., “Postal Address Finding and Reading,” Electronic Imaging East 90, Boston, MA, 1990, pp. 208-211. 3. Pawlicki, T., and S. N. Srihari, “Connectionist Neural Network Approach,” Workshop on Systems and Signal Processing, Bangalore, India, January 1988. 4. Shapiro, S. C., S. N. Srihari, J. Geller, and M.-R. Taie, “A Fault Diagnosis System Based on an Integrated Knowledge Base,” IEEE Software, March 1986, pp. 48-49. 5. Srihari, S. N., W. I. Rapaport and D. Kumar, “Natural Language Processing Using SNePS and Its Relevance to Sanskrit Grammatical Analysis,” First National Conference on Knowledge Representation and Inference in Sanskrit, Bangalore, India, December 1986. 6. Xiang, Z., and S. N. Srihari, “Diagnosis Based on Empirical and Model Knowledge,” IEEE Software, March 1986, pp. 50-51. (Computation and its application to handwritten digit recognition, Indo-U.S.) 7. Shapiro, S. C., S. N. Srihari, M.-R. Taie and J. Geller, “Development of an Intelligence Maintenance Assistant,” SIGART Newsletter, 92, April 1985, pp. 48-49.

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8. Srihari, S. N., J. J. Hull and R. Choudhari, “An Algorithm for Integrating Diverse Knowledge Sources in Text Recognition,” ACM Conference Office Information Systems, Philadelphia, 1982, pp. 46-54. 9. Herman, G. T., S. N. Srihari and J. K. Udupa, “Detection of Changing Boundaries in Two and Three Dimensions,” Workshop Computer Analysis Time-Varying Imagery, Philadelphia, 1979, pp. 14-16. 10. Srihari, S. N., “An Efficient Measurement Selection for Invariant Pattern Recognition,” Fourth International Cybernetics and Systems Congress, Amsterdam, Netherlands, 1978, pp. 67-68. 11. Srihari, S. N., “Use of Majority-vote in N-Sample Decision-making,” IEEE International Symposium Information Theory, Ithaca, NY, 1977, p. 29. 12. Srihari, S. N., and L. J. White, “Statistical Classifier Design for Aircraft Identification,” Third ACM Computer Science Conference, Washington, DC, 1975, p. 57.

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10. GRANTS AND CONTRACTS AS PRINCIPAL INVESTIGATOR

2017-2002 Project Title Funding Source Amount Period 1 Development of Individual Handwriting Characteristics in 1800 National Institute of Justice $235,000 2012-15 Students: Statistical Analysis and Likelihood Ratios That Emerge (NIJ)/State of Minnesota Over an Extended Period of Time 2 Statistical Characterization of Handwriting Characteristics National Institute of Justice $425,077 2010-12 (NIJ) 3 Quantitative Measures in Support of Latent Print Comparison NIJ $498,784 2009- 2012 4 Computational Methods for the Assessment of Handwriting NIJ $668,806 2004-10 5 Quantitative Assessment of the Individuality of Friction Ridge NIJ $596,478 2005-08 Patterns 6 Analysis of Footwear Impression Evidence NIJ $350,172 2007-10 6 Recognition of Handwritten Words in School Essays using National Science Foundation $100,000 2007-08 Conditional Random Fields (NSF) 7 IES and Other Support for APPS programs United States Postal Service $405,955 2007-08 (USPS) 8 Comparative evaluation of DQI and other Recognition Programs USPS $462,000 2007-08 9 Complex Document Information Processing DOE (Batelle subcontract) $12,820 2005-06 10 Handwriting Recognition Technology Assessment for Arabic and CIA $45,000 2006 Chinese 10 Creation of Arabic Corpus In-Q-Tel $50,000 2004-05 11 Digital Camera use in Barcode Imaging USPS $409,867 2003-07 12 Image Collection and Truthing USPS $3,906,541 2003-07 13 Flats Image Collection and Truthing USPS $1,499,471 2003-07 14 Alternate Keying Strategies USPS $165,000 2004-05 15 Reply Card Scanning USPS $210,000 2003-04 16 Quantitative Assessment of the Discriminatory Power of NIJ $298,237 2002-04 Handwriting and Validating Identification Procedures 17 Personal Name Lookups USPS $1,204,000 2001-03 18 Comparison Study of Barcodes USPS $470,000 2003-05 19 UK Address Interpretation Lockheed Martin (LM) $15,000 2003 20 Image evaluation Systems-Flats USPS $340,000 2002-03 21 Micropayment Processing USPS $1,204,000 2001-03 22 HWAI Plus Siemens $317,000 2002-03 23 AAPS Parcel Address Recognition Siemens $90,000 2002 24 Canadian Postcode Interpretation Siemens $50,000 2000-01 25 Handwritten Address Interpretation Siemens $300,000 2000-01 26 Canadian Postcode Recognition System House Ltd $10,000 1994 27 Mailpiece Library USPS $190,000 2002 28 Evaluation of Identification Codes USPS $133,000 2001 29 Return Merchandise System USPS $300,000 2001-02 30 Image Evaluation System Development USPS $1,850,583 199-03 31 Information-based Indicia USPS $300,000 1999-01 32 UK Address Interpretation LM $1,245,000 2000-02 SUB-TOTAL $17,697,714

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2001-1997 32 RCR/HWAI LM $660,000 2000-01 33 SDMM Directory Generation and Validation LM $44,235 2000-01 34 Image Truthing USPS $1,102,000 2000-02 35 Address Interpretation Systems for UK Program LM $1,224,367 2000 36 Handwriting Identificiation: Validity of NIJ $428,328 1999-01 Individuality and Computer-assisted Procedures 37 HWAI Control Strategy LM $129,190 1999-00 38 PROZE Character Recognition Improvements LM $128,395 1999-00 39 VRR Word Recognition Improvements LM $42,590 1999-00 40 Last Line and Foreign Processing LM $101,417 1999-00 41 RCR/HWAI Improvements LM $503,480 1999-00 42 UKAI Initial Tasks-Parsing and Resolution LM $152,442 1999-00 43 Truthing for Recognition Improvement Plan USPS $75,000 1999-00 44 Truthing and Analysis of Mailpiece Images USPS $290,636 1999-00 45 New Image Evaluation System USPS $395,257 1999-00 46 Implementation of Semi-automated Encoding USPS $185,261 1999-00 47 Sender Information Processing USPS $134,167 1999-00 48 Equipment Grant USPS $46,200 1999-00 49 Travel Grant USPS $34,103 1999-00 50 HWAI of Australian Addresses LM $218,333 1999 51 Last Line, Foreign Processing LM $100,412 1999 52 Image Processing Functions LM $69,156 1999 53 Control Strategy LM $101,468 1999 54 Word Recognizer LM $46,541 1999 55 New Character Recognition LM $45,019 1999 56 HWAI of Australian Addresses LM $319,959 1999 57 Gray Scale Image Processing USPS $790,000 1998-00 58 Address Truthing Analysis USPS $1,424,641 1998-00 59 HWAI Control Structures LM $79,200 1998-99 60 Database Enhancement LM $52,500 1998-99 61 New Parsing Techniques LM $77,500 1998-99 62 New Word Recognition Techniques LM $132,000 1998-99 63 New Character Recognition LM $88,000 1998-99 64 RCR/HWAI Improvements LM $400,000 1998-99 65 HWAI porting to NT LM $28,586 1998-99 66 HWAI Recognition Co-processor USPS $650,000 1998 67 HWAI of Australian Addresses LM $1,144,418 1997-98 68 RCR/HWAI Integration LM $1,500,000 1997-98 69 HWAI PC Integration USPS $494,924 1997-98 70 HWAI/RCR Research LM $550,860 1997-98 71 HWAI/RCR LM $407,686 1997 SUB-TOTAL $14,398,271

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1997-1983 72 Directory Compression USPS $37,959 1997 73 Image Analysis USPS $40,722 1997 74 Recognition through Evolutionary USPS $57,410 1997 Computing 75 HWAI PC Porting USPS $215,497 1997 76 HWAI RCR USPS $585,924 1996-97 77 HWAI/RCR Integration LM $596,474 1996-97 78 HWAI PC Integration Task 1 USPS $255,076 1996-97 79 HWAI Integration Testing USPS $99,750 1996-97 80 Improvements in HWAI USPS $2,510,681 1993-96 81 Reply Card Processing-Phase III USPS $1,388,534 1995-96 82 Reply Card Processing PIMS USPS $1,435,416 1993-95 83 Handwritten Text Recognition National Security $532,939 1994-96 Agency (NSA) 84 Document Analysis and Recognition Xerox Corp $70,000 1993-00 85 Recognitiion of Handprinted Forms Reader's Digest $10,000 1994 86 Interactive Service Research Support USPS $1,299,519 1993-96 87 CEDAR Supplemental Activities USPS $750,000 1991-95 88 HWAI Research USPS $3,256,837 1991-94 89 PENMAN: Handwritten OCR NSA $423,536 1994-96 90 Japanese Optical Character Recognition NSA $805,706 1993-96 91 Universal Message Routing System USPS $988,128 1993-96 92 Reply Card Processing USPS $2,781,416 1993-97 93 Implementation for RCR Application USPS $2,209,688 1993-95 94 SCRIPS; Name and Address Block Reader Grumman Data $1,960,723 1994-96 Sy stems 95 CEDAR Supplementary Funds USPS $750,000 1992-93 96 Laboratory Address Recognition Unit USPS $1,000,000 1991-92 97 Machine-Printed Character Recognition USPS $1,724,687 1991-92 98 Handwritten Address Interpretation USPS $3,000,000 1991-94 99 Knowledge-Based Document Image NSF $185,000 1991-93 Understanding 100 Recognition of Handwritten Address ZIP USPS $1,750,000 1986-90 Codes 101 Advanced Address Block Location USPS $690,000 1985-88 102 Expert Automated Maintenance System RADC $819,000 1984-89 (Shaprio, PI) 103 AI-Graphics Interface for Rule-based RADC $52,266 1984-85 system (Shapiro, PI) 104 Advanced Character Recognition USPS $248,000 1984-85 105 Contextual Algorithms for Text NSF $54,800 1980-83 Recognition SUB-TOTAL $32,585,688 Grand Total = $ 64,307,889

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11. DOCTORAL STUDENTS SUPERVISED

Most recent listed first.

1. Jun Chu, Representation Learning and Data Augmentation in Forensic Comparison. 2018, Facebook, Mountainview, CA. 2. Junfei Wang, Improving Large-Scale Recommendation Systems with Contextual Signals, 2017, Facebook, Seattle, WA. 3. Zhen Xu, Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model, 2016, Google, Mountain View, CA. 4. Gang Chen, Sequential Classification using Deep Learning, 2015 Amazon, Seattle, WA. 5. Yu Liu, A Probabilistic Similarity Measure for Latent Fingerprints, 2014. EPIC Systems, Madison, WI. 6. Yi Tang, Evaluating the Probability of Identification in Forensic Science, 2012, Microsoft, Redmond, WA. 7. Chang Su, Machine Learning in Fingerprint Probability Models, Computer Science and Engineering 2011. Member of Technical Staff, E-bay, Santa Clara, CA. 8. Harish Srinivasan, Machine Learning Approaches to Person Identification with Applications to Forensic Document Analysis, 2008. Amazon, Seattle, WA. 9. Chen Huang, Content-based Handwritten Document Indexing and Retrieval, 2008 10. Gregory Ball, Arabic Handwriting Recognition using Machine Learning Approaches, 2007, CEDAR. 11. Siyuan Chen, Signature Verification using Flexible Template Matching Approaches, 2006. 12. Catalin Tomai, A Computational Theory of Visual Word Recognition, 2003. Microsoft Corp, Seattle. 13. Bin Zhang, Handwriting Pattern Matching and Retrieval with Binary Features, 2003. Icahn School of Medicine, New York, NY. 14. Sung-Hyuk Cha, Use of Distance Measures in Handwriting Analysis, 2001. Pace University. 15. Minchul Jung, Font Classification ad Character Segmentation for Postal Address Reading, 2001. 16. Jaehwa Park, Hierarchical Character Recognition and Its Use in Word/Phrase Recognition, 1999. University, Korea. 17. Uma Mahadevan, Robust Vision through Imperfect Eyes: A System for Processing City, State and ZIP Code Fields in Handwritten Addresses., 1998. 18. Jung Soh, A Theory of Document Object Locator Combination, 1998. Defense Research Institute, South Korea. 19. Jeon-Man Park, Address Block Location System Using Multi-Resolution State-Space Search, 1997. Samsung Data Systems, South Korea. 20. Ajay Shekhawat, A Framework for Handwritten Document Recognition, 1997, Yahoo, Inc, Mountain View, CA. 21. Gyeonghwan Kim, Recognition of Offline Handwritten Words and Its Extension to Phrase Recognition, 1996. Sogang University, South Korea. 22. Sriganesh Madhvanath, Histolic Techniques for Handwritten Word Recognition Engines, Computer Science; 1996. , IBM, Almaden Research Center, Almaden, CA. 23. Dar-Shyang Lee, A Theory of Classifier Combinations: The Neural Network Approach, Computer Science; 1995. Google, Inc., Mountainview, CA. 24. Jenchyou Lii, Use of Character Recognition and Syntax in Locating Address Paragraphs in Complex Documents, 1995. ESS, CA. 25. Ying Liu, Document Image Binarization Based on Texture Analysis, 1995. ADT, St. Louis, MO. 26. Stephen Lam, A Computational Framework for Adaptive Reading in Document Image Understanding, 1994. Enterpreneur, Hong Kong.. 27. Debashish Niyogi, A Knowledge-Based Approach to Deriving Logical Structure from Document Images, 1994. Oracle Corporation, San Mateo, CA. 28. Geetha Srikantan, Image Sampling Rate and Pattern Recognition, 1994. Sun Microystems, Mountain View, CA. 29. Xin Zhao, Machine-Printed Word Recognition Using Ideal Word Patterns and Lexical Reduction; 1994. Oracle Corporation, San Mateo, CA. 30. Mou-Yen Chen, Handwritten Word Recognition Using Hidden Markov Models, 1993. 31. John Favata, Recognition of Handwritten Words Using Multi-Level Generate-and-Test, 1993. SUNY College, Buffalo, NY. 32. Jiah-Shing Chen, A Probabilistic Theory of Model-Based Diagnosis, 1992. Chungliu University, Taiwan. 33. Edward Cohen, Interpreting Handwritten Text in a Structured Environment, Computer Science; 1992. Software Division, Tritech Technologies. 34. Venugopal Govindaraju, Computational Theory for Locating Human Faces in Photographs, 1992. SUNY at Buffalo. 35. Tin-Kam Ho, Theory of Multiple Classifier Systems and Its Application to Visual Word Recognition, Computer Science; 1992. Lucent Bell Labs, Murray Hills, NJ. April 16, 2020 29

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36. Jonathan J. Hull, A Computational Theory of Visual Word Recognition, Computer Science; 1988. Ricoh Corporation, Menlo Park, CA. 37. Ching-huei Wang, Object Recognition in a Visually Complex Environment and Its Application to Locating Address Blocks. Boeing, Seattle, WA 38. Zhigang Xiang, Multi-Level, Model-Based Diagnostic Reasoning, Computer Science; 1988. Queens College, CUNY, New York, NY. 39. Mingruey R. Taie, Representation of Device Knowledge for Versatile Fault Diagnosis, Computer Science; 1987. AT&T Bell Labs, Middletown, NJ. 40. Radmilo M. Bozinovic, Recognition of Cursive Script: A Case of Multi-Level Perception, Computer Science; 1985. Apple Computer Corporation, Cupertino, CA. 41. Mann-May Yau, Hierarchical Representation of Three Dimensional Digital Objects, Computer Science; 1983. AT&T Bell Labs, Middletown, NJ.

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12. INVITED LECTURES AND CONFERENCE PRESENTATIONS

Date Title Organization/Auspices Location

Mar 11, 2020 Probabilistic Knowledge Graphs NIST Ontology Summit Online July 26, 2019 Explainable AI Deep Learning Summer School Warsaw, Poland June 21, 2019 Artificial Intelligence IISc Global Summit Palo Alto, CA April 10, 2019 Explainable AI NIST Ontology Summit Gaithersberg, MD Feb 20, 2019 Modern Machine Learning National Communications Conf Bangalore, India Feb 18, 2019 Artificial Intelligence University of Mysore Endo Lec Mysore, India Oct 5, 2018 Artificial Intelligence Buffalo Niagara Medical Center Buffalo, NY July 20, 2018 Artificial Intelligence Ek Step Bangalore, India July 17, 2018 Artificial Intelligence and Deep Learning Ind. Inst Science, Public Lecture Bangalore, India May 9, 2018 Artificial Intelligence and Deep Learning Peace Tech Summit Washington, DC Jun 4-25, 2018 Deep Learning Lecture Series Indian Institute of Science Bangalore, India Jan 10, 2018 Representation Learning Int Conf Pattern Recog and AI Bangalore, India Aug 3, 2017 Short course on Deep Learning Indian Inst of Info. Technology Allahabad, India June 25, 2017 Artificial and Machine Intelligence Data Intelligence: Practioner ML McLean Va June 5, 2017 Artificial Intelligence National Institute of Standards Gaithersburg, MD April 25, 2017 Machine Learning: Overview Praxair Buffalo, NY June 1, 2016 Towards a Forensic Data Science NIST Gaithersburg, MD Mar 24, 2014 Uncertainty in forensic identification IBM Research Labs. Valletta, Malta Learning Causality Biometrics: Theory, Apps Syst Jan 13, 2014 Evaluating Likelihood Ratios in Forensic ID NIST Bangalore, India Oct 2, 2013 Interactive Writer Ident-CEDAR-FOX Advanced Pat. Recog Washington DC system & Historical Handwrit. Wkshp June 4, 2013 Writer Id of Historical Documents AAFS Gaithersburg, MD

May 21, 2013 Statistical Char of Handwritten Items Erlangen, Germany Washington DC Feb 21, 2013

Combining Evidence using Likelihood Document Recognition and Feb 5, 2013 San Francisco, CA Ratios in Writer Verification Retrieval Conference Learning Probabilistic Graphical Models Nov 21, 2012 Indian Institute of Science Bangalore, India from Data Methods for Incorporating Evidence into International Conference on Nov 13, 2012 Tsukuba, Japan Posterior Scoring of Hypotheses Pattern Recognition International Conference on Sept 21, 2012 Evaluating the Probability of Identification in Frontiers in Handwriting Bari, Italy the Forensic Sciences Recognition

Document Recognition and Jan 28, 2012 Questioned Document Workflow: Example San Francisco, CA Retrieval Conference of the Lindbergh case Probabilistic Graphical Models and Social Indo-US Workshop of Large Dec 19, 2011 Networks Scale data Analytics and Bangalore, India Intelligent Services Probabilistic Graphical Models in Machine Sept 25,2011 Department of Biostatistics Buffalo, NY Learning

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Probabilistic Graphical Models in Machine International Conference on Sept 18, 2011 Beijing, China Learning Document Anal. Recognition Probabilistic Graphical Models in Machine April 28, 2011 Acharya Institute of Technology Bangalore, India Learning (I) Statistical Characterization of Handwriting Document Recognition and Jan 28, 2011 San Francisco, CA Characteristics using Automated Tools Retrieval Conference Evaluation of Rarity of Fingerprints (Poster) Neural Information Processing Dec 6, 2010 Vancouver, BC Systems (NIPS) Nov 16-18, Writer Verification of Historical Documents Int Conf on Frontiers in Kolkata, India 2010 among Cohort Writers Handwriting Recognition Latent Fingerprint Core point prediction International Conference on Aug, 2010 Istanbul, Turkey using Gaussian Processes Pattern Recognition Impression and Pattern Evidence Symposium Clearwater Beach, Aug 6-8, 2010 NIJ (I) FL Content-Based Retrieval OF Footwear July 16, 2010 Indian Institute of Science Bangalore, India Images (I) July 15, 2010 Statistics and data Mining (I) Amrita University Bangalore, India Impression Evidence: Strengthening the June 14, 2010 NIJ Conference Arlington, VA Disciplines through Research - Panel (I) Computational Forensics (I) Computational Modeling of May 7, 2010 Buffalo, NY Objects in Images(CompImage ) Software Tools for Crime Scene Gifted Math Program 25th Mar 10, 2010 Buffalo, NY Investigation (I) Anniversary Probability Models for Pattern and Jan 29, 2010 DOJ Indigent Symposium Washington, DC Impression Evidence (I) Comparison of Historical Documents for SPIE Document Recognition Jan 21, 2010 San Jose, CA Writership and Retrieval Conference Dec 14, 2009 Machine Learning (I) Infosys Bangalore, India Gaussian Processes: Tutorial and Indian Institute of Science Dec 11, 2009 Bangalore, India Applications (I) (School of CSA) Machine Learning and Pattern Recognition Adobe India Distinguished Dec 11, 2009 Bangalore, India (I) Lecture Machine Learning (I) Dec 7, 2009 National University of Malaysia Putrajaya, Malaysia Recent Developments in Pattern Recognition Int Conf Soft Computing and Dec 6, 2009 Malacca, Malaysia and Machine Learning Pattern Recognition Computational Forensics (I) Dec 4, 2009 University of Putra Putra, Malaysia Document Analysis and Recognition (I) University of Technology Dec 1, 2009 Skudai, Malaysia Malaysia Computational Forensics (I) Sept 29, 2009 National Institute of Justice Washington D.C. Computational Analysis of Shoe-print International Association for Aug18, 2009 Tampa, FL Images (I) Identification 1. Discriminability of Fingerprints of Twins International Workshop on August 13-14, The Hague, The 2. Bayesian Signature Verification, Computational Forensics 2009 Netherlans 3. Individuality of Fingerprints (Netherlands Forensic Institute) Semi-supervised Learning for Handwriting International Conference on July 26, 2009 Recognition Document Analysis and Barcelona, Spain Recognition Computational Methods for Analysis of July 2, 2009 Shoe-print Evidence (I) Foster & Freeman Evesham, England Writer Verification and Identification (I) June 30, 2009 Telecom Paris Tech Paris, France

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Case-work with CEDAR-FOX (I) Southeast Association of April 16, 2009 Atlanta, GA Forensic Document Examiners Generative Models and Probability April 13, 2009 Evaluation in Forensics Indian Institute of Science Bangalore, India Machine Learning in the Oil Industry (I) Dhahran, Saudi April 8, 2009 Saudi ARAMCO Arabia April 4-7, Machine Learning Short Course (I) King Fahd University of Dhahran, Saudi 2009 Petroleum and Minerals Arabia Probability of Random Correspondence in March 9, 2009 Fingerprints (I) San Jose State University San Jose, CA

February 19, Individuality of Handwriting: A Twin’s American Academy of Forensic Denver, CO 2009 Study (I) Sciences January 20, Comparison of Statistical Models for Writer Document Recognition and San Jose, CA 2009 Verification Retrieval XVI December 9, Generative Models for Fingerprint International Conference on Tampa. FL 2008 Individuality using Ridge Models Pattern Recognition December 3, Language Independent Word Spotting in Asia-Pacific Conference on Bali, Indonesia 2008 Scanned Docuemnts Digital Libraries October 23, Artificial Intelligence in the Post Office and Telcordia Piscataway, NJ 2008 the Police Department (I) Machine Learning using Bayesian September 24, Approaches (I) Indian Institute of Science Bangalore, India 2008 September 16, Automatic Verification of Handwritten International Workshop on Nara, Japan 2008 Arabic Document Analysis Systems August 20, Computational Approaches to Shoeprint International Association for Louisville, KY 2008 Verification (I) Identification Panel on “Confirmation Bias in Fingerprint National Institute of Justice July 21, 2008 Arlington, VA Examination” (I) Conference Computational Forensics The Hague, The June 1, 2008 Netherlands Forensic Institute Netherlands Machine Learning: New Paradigms and Lund University Mathematical May 29, 2008 Lund, Sweden Perspectives (I) Sciences Computational Forensics (I) May 27, 2008 Grojvik University Grojvik, Norway Computational Forensics (I) May 26, 2008 Kripos Oslo, Norway Machine Learning: New Paradigms and April 30, 2008 Perspectives (I) Yahoo! Bangalore, India Machine Learning: New Paradigms and April 29, 2008 Perspectives (I) Infosys Bangalore, India Machine Learning: New Paradigms and International School of April 28, 2008 Mysore, India Perspectives (I) Information Management April 21-25, Machine Learning Workshop (Five day solo International School of Bangalore, India 2008 workshop with 35 participants) (I) Information Management CEDAR-FOX System (One-day workshop Southwest Association of April 12, 2008 San Diego, CA with 30 participants) (I) Forensic Document Examiners February 18, Computational Methods for Handwritten American Academy of Forensic Washington DC 2008 Questioned Document Examination (I) Sciences

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1. Writer Adaptation in Handwritten Arabic Document Recognition and January 31, Recognition 2. Robust segmentation of Retrieval XV San Jose, CA 2008 handwritten lines 3. Handwritten word segmentation using local and global features Segmentation of Overlapping Handwritten International Graphonomics Melbourne, Nov 12, 2007 Lines Society Australia Computing Strength of Evidence in Writer International Conference on Sep 25, 2007 Curitiba, Brazil Verification Document Analysis and Recog Computational Forensics: Towards Hybrid Int Workshop on Computational Aug 30, 2007 Manchester, UK Intelligent Crime Solving Forensics July 25, 2007 Individuality of Fingerprints: Generative International Association for San Diego, CA Models and Twins Studies Identification May 1, 2007 Computational Approaches to Scoring Pearson Knowledge Boulder, CO Handwritten Responses in Reading Technologies Comprehension Tests May 1, 2007 Computer Processing of Handwriting in University of Colorado Institute Boulder, CO Documents (I) for Cognitive Sciences April 9, 2007 Use of Ridge Points in Partial Fingerprint Biometric Technology for Orlando, FL Matching Human Identification IV April 4, 2007 Computational; Methods for the Comparison National Institute of Justice Garden Grove, CA of Extended Handwriting and Signatures Applied Technology Conference March 16, Language Models for Text Recognition (I) University of Mysore, Mysore, India 2007 International School of Information Management February 26, Pattern Recognition and Machine Learning Pitney Bowes Research Middlebury, CT 2007 February 1, 1. A Statistical Method of Line Segmentation Document Recognition and San Jose, CA 2007 2. Segmentation of Documents using Retrieval XVI Conditional Random Fields January 31, Machine Learning in Language Related Google Mountain View, 2007 Technologies (I) CA January 10, On the Automatic Scoring of Handwritten International Joint Conference Hyderabad, India 2007 Essays on Artificial Intelligence January 4, Meeting of the Minds: Machine Learning in Hewlett Packard Research Bangalore, India 2007 Language-related Technologies (I) Laboratory December 29, Meeting of the Minds: Machine Learning in International Symposium on Bangalore, India 2006 Language-related Technologies (I) Cognition and Recognition December 22, Meeting of the Minds: Machine Learning in Indian Institute of Technology Mumbai, India 2006 Language-related Technologies (I) December 16, Machine Learning for Signature Verification International Conference on Madurai, India 2006 Graphics, Vision and Image Processing December 8, New Paradigms in Pattern Recognition (I) International Conference on Hubli, India 2006 Signal and Image Processing November 4, Panel on Legal Issues in Fingerprint National Conference on Science, St Petersburg, FL 2006 Identification (I) Technology and Law October 24, Mapping Transcripts to Handwritten Text International Workshop on La Baule, France 2006 Frontiers in Handwriting Recognition September 29, Conditional Random Fields in Document Descartes Conference on Washington, DC 2006 Retrieval (I) Mathematical Models in Counter-terrorism September 28, Versatile Retrieval of Arabic Documents Symposium on Arabic and College Park, MD 2006 Chinese Handwriting August 9, Automatic Interpretation and Assessment of Educational Testing Service Princeton, NJ 2006 Handwritten Answer Documents

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July 4, 2006 Quality of Minutiae and Verification International Association for Boston, MA Accuracy Identification April 27, 2006 Document Image Retrieval using Signatures Document Image Analysis for Lyons, France as Queries Libraries April 21, 2006 Computer Processing of Handwriting in Michigan State University East Lansing, MI Documents Computer Science Department Distinguished Lecture Series April 17, 2006 ROC and Likelihood Methods in Fingerprint Biometric Technology for Orlando, FL Identification Human Identification III (SPIE) February 14, Scoring Handwritten School Essays using Document Analysis Systems VII Nelson, New 2006 LSA Workshop Zealand January 31, Writer Verification and Identification NIJ Technology Partnership Hilton Head, SC 2006 Workshop January 18, Spotting Words in Handwritten Arabic Document Recognition and San Jose, CA 2006 Documents Retrieval XIII December 29, Computer Processing of Handwriting in International Institute of Hyderabad, India 2005 Documents Information Technology December 27, Malnad Engineering College Hassan, India 2005 December 22, International Conference on Mysore, India 2005 Cognition and Recognition November 11, European Federation of Budapest, Hungary 2005 Handwriting Examiners November 3, Symposium Document Image College Park, MD 2005 Understanding Technology September 1, Int Conference on Document Seoul, Korea 2005 Analysis and Recognition August 13, American Society of Questioned Montreal, Canada 2005 Document Examiners June 27-28, International Graphonomics Salerno, Italy 2005 Society Conference June 23, 2005 UB Summer Lecture Series Buffalo, NY June 13, 2005 Florida Department of Education Tallahassee, FL April 7, 2005 MITRE Workshop on Optical McLean, VA Handwriting Recognition March 29, Complex Document Image Chicago, IL 2005 Processing Workshop March 30, SPIE Conference on Homeland Orlando, Florida 2005 Security Mar 10, 2005 Indian Institute of Science Bangalore, India March 8, 2005 International Workshop on Calcutta, India Document Analysis February 21, American Academy of Forensic New Orleans, LA 2005 Sciences January 19, Society of Photo-Instrumentn San Jose, CA 2005 Engineers-DRR 13 December Conference on Lateral Bangalore, India 2004 Computing December Int. Conf. Knowledge Based Hyderabad, India 2004 Computer Systems November International Workshop Tokyo, Japan 2004 Frontiers in Handwriting Recog September Int Workshop on Document Florence, Italy 2004 Analysis Systems September Joint meeting of MAFS, Orlando, FL 2004 MAAFS, CAFS, SAFS

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August 2004 International Conference on Cambridge, Pattern Recognition England June 22, 2004 Biometric Technologies-2004 Calgary, Canada June 14, 2004 Institute for Defense Analysis Alexandria, VA Mar 12, 2004 University of Maryland College Park, MD February 17, American Academy of Forensic Dallas, TX 2004 Sciences January 2004 Document Image Analysis for Palo, Alto, CA Libraries January 21, Tenth Int. Conf. on Doc. Santa Clara, CA 2004 Recognition Retrieval (SPIE) Dec 11, 2003 Indian Statistical Institute Calcutta, India November 3, International Graphonomics Scottsdale, AZ 2003 Society September 25, European Association of Istanbul, Turkey 2003 Forensic Sciences August 24, American Society of Questioned Baltimore, MD 2003 Document Examiners August 5, International Conference on Edinburgh, 2003 Doc.Analysis and Recog. Scotland May 7, 2003 National Security Agency Columbia, MD May 6, 2003 FBI Academy Quantico, VA April 11, 2003 Symposium on Document Image Greenbelt, MD Understanding February 2003 American Academy of Forensic Chiacago, IL Sciences October 2002 Indian Institute of Science Bangalore, India April 27, 2002 Southwest Association of San Diego, CA Forensic Document Examiners February 2002 American Academy of Forensic Atlanta, GA Sciences January 21-22, Ninth Int. Conf. on Doc. San Jose, CA 2002 Recognition Retrieval (SPIE) November 9, Canadian Forensic Sciences Toronto, Canada 2001 Conference November US Postal Inspection Service Washington, DC 2001 October 2001 Indian Institute of Science Bangalore, India September 10- Sixth Int. Conf. on Doc. Seattle, WA 13, 2001 Analysis and Recognition July 27, 2001 US Secret Service Washington, DC July 20, 2001 US Postal Inspection Service Washington, DC April 24, 2001 Symp. Document Image Annapolis, MD Understanding Technology February 21, American Academy of Forensic Seattle, WA 2001 Sciences April 14, 2000 University of Southwestern Baton Rouge, LA Louisiana March 16-19, Int. Conf. in honor of Prof. C. R. San Antonio, TX 2000 Rao February 20, Annual National Institute of Reno, NV 2000 Justice Grantees Meeting December 23, Indian Statistical Institute Calcutta, India 1999 November University of Rochester Rochester, NY 1999 Computer Science Colloquium

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September 20- Fifth Int Conference Document Bangalore, India 22, 1999 Anal and Recognition August 15-16, Purdue University Advances W. Lafayette, IN 1999 Image Proc Understanding January 5-7, Second International Conference Hong Kong 1999 on Multimodal Interface August 16-20, International Conference on Brisbane, Australia 1998 Pattern Recognition Oct 15, 1997 SUNY at Buffalo Buffalo, NY August 18-20, Fourth Int. Conf. Document Ulm, Germany 1997 Analysis and Recognition August 25-29, Thirteenth Int. Conference of Vienna, Austria 1997 Pattern Recognition August 1997 United States Postal Service Buffalo, NY June 1997 Epcot Center Orlando, FL April 30, 1997 Symposium Document Image Annapolis, MD Understanding Technology April 23-25, Int. Conf. Computer Systems Hsinchu, Taiwan 1997 for Industrial Applications March 3-4, United States Postal Service Rochester, NY 1997 February 10- Int Conf Computational Gold Coast, 12, 1997 Intelligence Multimedia Appls. Australia Nov 20, 1996 University of Mysore Mysore, India Oct16-29, University of Bari Bari, Italy 1996 September 2- Fifth Int Conf. Frontiers in Colchester, England 5, 1996 Handwriting Recognition October 15, Third Int. Conf. Document Montreal, Canada 1995 Analysis and Recognition February 28, Concordia University, CS Montreal, Canada 1995 Department February 9, Information Sciences Institute, Los Angeles, CA. 1995 USC Feb 8, 1995 SPIE Conference San Jose, CA December 8, International Workshop Tapei, Taiwan 1994 Handwriting Recognition Dec 5, 1994 Yonsei University Seoul, S. Korea October 10, Document Analysis Systems Kaiserslautn, 1994 Conference Germany Oct 5, 1994 Tata Consultancy Services Bombay, India September 30, Indian Institute of Science Bangalore, India 1994 June 20, 1994 Digital Libraries Conference College Station, TX May 19, 1994 Digital Libraries Conference Newark, NJ February 10, SPIE Conference San Jose, CA 1994 October 22, Int. Conf. on Document Tsukuba , Japan 1993 Analysis and Recognition August 18, National Library of Medicine Bethesda, MD 1993 May 14, 1993 SUNY at Stony Brook Stony Brook, NY April 25, 1993 Document Anal and Information Las Vegas, NV Retrieval Symposium April 1, 1993 Princeton University Princeton, NJ Jan 4, 1993 Indian Institute of Science Bangalore, India

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July 9, 1992 DARPA Workshop on Man- Endicott, MA Machine Communications May 12, 1992 University of North Carolina - Charlotte, NC IBM Symposium May 6, 1992 DARPA Workshop on Palo Alto, CA Document Understanding Jan 28, 1992 Ricoh Corporation Kawasaki, Japan January 26, Institute for Posts and Tokyo, Japan 1992 Telecommunications Policy October 1, First Int. Conf. Document St. Malo, France 1991 Analysis and Recognition December 18, Knowledge Based Computer Pune, India 1990 Systems IV November 6, USPS Advanced Technology Washington, DC 1990 Conference October 30, Electronic Imaging East Boston, MA 1990 May 16, 1990 Vision Interface Halifax, Canada April 2, 1990 Int. Workshop on Frontiers of Montreal, Canada Handwriting Recognition December 11, Int. Conference on Knowledge Bombay, India 1989 Based Computer Systems October 18, Association Intelligent System Syracuse, NY 1989 Technologies September 25, Science Research Automation Leningrad, USSR 1989 Council September 8, COST-13 Summer School on Bonas, France 1989 From Pixels to Features August 15, Northeast Artificial Intelligence Blue Mtn. Lake, 1989 Consortium Conference NY June 12, 1989 Image Understanding Machine Cape Cod, MA Vision (OSA Meeting) June 5, 1989 IEEE-CS Computer Vision San Diego, CA Pattern Recognition Conf. Jan 19, 1989 MITRE Corporation McLean, VA November 30, South East Asia Regional New Delhi, India 1988 Computer Confederation Conf. Oct 24, 1988 AT&T Bell Laboratories Murray Hill, NJ September 6, CAS Int. Seminar on Artificial Dubrovnik, 1988 Intelligence Yugoslav. August 24, COST-13 Workshop on From Bonas, France 1988 Pixels to Predicates May 30, 1988 Eighth International Workshop Avignon, France on Expert Systems January 8, Indo-US Workshop on Systems Bangalore, India 1988 and Signal Processing January 4, Image Processing & AI Seminar Hyderabad, India 1988 - Indotronix Corp. December 29, Tata Research Design and Pune, India 1987 Development Center October 28, Int. Workshop on Expert Novosibirsk, USSR 1987 Systems & Pattern Recognition August 25, International Joint Conference Milan, Italy 1987 on Artificial Intelligence May 21, 1987 Society of Photographic Rochester, NY Scientists and Engineers

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May 11, 1987 Seventh International Workshop Avignon, France on Expert Systems April 9, 1987 USPS Advanced Technology Washington, DC Advisory Board January 6, Institute of Electronics and Bangalore, India 1987 Telecom. Engineers January 6, Indian Institute of Science, ECE Bangalore, India 1987 Department December 30, Indian Institute of Technology, Madras, India 1986 Department of CS December 20, Conf. Knowledge Represent. Bangalore, India 1986 and Inference in Sanskrit November 20, ACM-IEEE Chapter Rochester, NY 1986 November 5, Fall Joint Computer Conference Dallas, Texas 1986 October 28, Eighth International Conference Paris, France 1986 on Pattern Recognition October 22, USPS Advanced Technology Washington, DC 1986 Conference October 15, SUNY Biophysics Department Buffalo, NY 1986 Sepember 20, Northeast Artificial Intelligence Buffalo, NY 1986 Consortium Conference July 10, 1986 Northeast Artificial Intelligence Rochester, NY Consortium Conference April 29, 1986 AEG-Telefunken Ulm, W. Germany April 28, 1986 Sixth International Workshop on Avignon, France Expert Systems April 19, 1986 AI Applications to Engineering Southampton, UK Mar 20, 1986 SUNY College at Brockport Brockport, NY December 10, Second Artificial Intelligence Miami Beach, FL 1985 Applications Conference November 4, University of Rochester, Dept. Rochester, NY 1985 of Computer Science October 23, Expert Systems in Government McLean, VA 1985 Symposium September 27, Xerox Webster Res. Center, Webster, NY 1985 Cognitive System Group September 11, Calspan - UB series (ECE Amherst, NY 1985 Department) Aug 20, 1985 Rome Air Development Center Rome, NY July 17, 1985 Northeast Artificial Intelligence Minnowbrook, NY Consortium Conference June 28, 1985 Arthur D. Little, Inc. Washington, DC June 28, 1985 USPS Technology Resource Washington, DC Department May 13, 1985 Fifth International Workshop on Avignon, France Expert Systems April 16, 1985 National Computer Graphics Dallas, TX Association Conference February 25, Goal-Directed Computer Vision Orlando, FL 1985 Workshop February 19, USPS Advanced Technology Washington, DC 1985 Conference December 18, Indian Institute of Science, Bangalore, India 1984 School of Automation

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December 17, Electronics Radar Development Bangalore, India 1984 Establishment (LRDE) December 10, International Conference Bangalore, India 1984 Computers, Systems August 1, Seventh International Montreal, Canada 1984 Conference on Pattern Recognition July 20, 1984 Xerox Webster Research Center, Rochester, NY Imaging Systems Lab June 4, 1984 AI: Relevance to Indian Industry Pune, India :TRDDC Wkshp May 28, 1984 University of Maryland, College Park, MD Computer Vision Laboratory April 1, 1984 University of Michigan, Ann Arbor, MI Department of EE and CS July 21, 1983 Multiresolution Image Leesburg, VA Processing & Analysis Workshop April 10, 1983 Honeywell Users Group Buffalo, NY January 12, Indian Institute of Technology, Madras, India 1983 Department of CS January 5, Indian Institute of Science, Bangalore, India 1983 School of Automation December 22, Tata Institute of Fundamental Bombay, India 1982 Research October10, International Conference on Seattle, WA 1982 Cybernetics and Society August 20, AAAI-82 National Conference Pittsburgh, PA 1982 on Artificial Intelligence June 21, 1982 ACM Conference on Office Philadelphia, PA Information Systems June 16, 1982 IEEE-CS Conference Pattern Las Vegas, NV Recognition & Image Processing June 8, 1982 AFIPS National Computer Houston, TX Conference August 3, IEEE-CS Conf. Pattern Dallas, TX 1981 Recognition & Image Processing June 10, 1981 Canadian Man-Computer Waterloo, Ontario Communications Society Conference December 1, Fifth International Conference Miami Beach, FL 1980 on Pattern Recognition October 8, International Conf. Cybernetics Cambridge, MA 1980 and Society (IEEE-SMC) October 10, International Conference Denver, CO 1979 Cybernetics and Society (IEEE- SMC)

August 7, 1979 IEEE-CS Conf. Pattern Recognition & Image Processing Chicago, IL Amsterdam, August 22, 1978 Fourth International Cybernetics and Systems Congress Netherlands July 20, 1978 Indian Institute of Science, School of Automation Bangalore, India June 1, 1978 IEEE-CS Conf.Pattern Recognition & Image Processing Chicago, IL March 5, 1978 Michigan State University, Department of CS East Lansing, MI January 20, 1978 ACM Computer Science Conference Detroit, MI October 7, 1977 IEEE International Symposium on Information Theory Ithaca, NY February 2, 1975 ACM Computer Science Conference Washington, DC

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