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Jacob Mayne Luber – Bioinformatics & Integrative Genomics

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Jacob Mayne Luber – Bioinformatics & Integrative Genomics Jacob Mayne Luber Harvard Medical School 10 Shattuck Street Boston, MA 02115 Bioinformatics & Integrative Genomics B scholar.harvard.edu/jluber Education July Ph.D. Bioinformatics and Integrative Genomics (2021), Harvard University, 2016–Present Cambridge, MA, 02138. Division of Medical Sciences @ HMS / The Graduate School of Arts and Sciences @ Harvard Summer 2016 Rotation: Huttenhower Lab, Department of Biostatistics, T.H. Chan School of Public Health 2012–2016 B.S. with Special Departmental Honors in Computer Science cum laude, Trinity University, San Antonio, TX. Trinity University Presidential Scholar Trinity University Mach Research Fellow President-Trinity University Chapter of Upsilon Pi Epsilon (honor fraternity of the Association for Computing Machinery) 2009-2012 High School Diploma, The Lawrenceville School, Lawrenceville, NJ. Awards Spring 2016 Trinity CS Department Senior Research Award, Trinity University. "Outstanding Senior Research Award – not awarded every year, this honor is given to recognize that senior who has a particularly distinguished record of Computer Science research." Spring 2016 Mach Research Fellowship, Trinity University. Annually, each academic department nominates one senior for the Mach, which recognizes outstanding undergraduate research achievement; of this candidate pool the Faculty Research Committee selects 5 recipients. I received the computer science department nomination and was one of the University wide recipients. Summer 2015 International Society For Computational Biology Travel Fellowship. ISCB awarded me a travel fellowship to attend and present my research at the 2015 Joint International Conference on Intelligent Systems For Molecular Biology and European Conference on Computational Biology. My application was selected out of a pool almost entirely comprised of PhD students and post-docs. Spring 2015 Trinity CS Department Junior Research Award, Trinity University. "Outstanding Junior Research Award – not awarded every year, this honor is given to recognize that junior who has a particularly distinguished record of Computer Science research." Fall 2014 GCURS Best CS Research Talk, Rice University. A panel comprised of Rice University CS faculty judged my talk at Rice’s annual undergrad- uate STEM conference to be the best talk in CS. Research Experience May 2014 – Hibbs Computational Biology Laboratory, Trinity University. June 2016 Work on large scale genomic data integration and machine learning (∼500B data points) in the context of finding new pathways that are related to osteoblast differentiation. Succesfully defended my honors undergraduate thesis "Improved Prediction of Mouse Pathways Related to Bone Maintenance Through Machine Learning Utilizing Diverse Genomic Data" in March 2016. Summer Bult Laboratory, The Jackson Laboratory. 2015-June 2016 Research consisting of data mining and machine learning work to identify novel cancer biomarkers for the Patient Derived Xenograft project at JAX. I built a computational framework that uses statistically sound machine learning techniques to correlate drug response with genome based signatures in Triple Negative Breast Cancer Patient Derived Xenograft models. Through validation of predicted results, we evaluated models based on unsupervised clustering, a per tumor bayesian integration method, and a per gene multi-class support vector machine method. August 2014 – Watson Economics Laboratory, Trinity University. August 2015 Ongoing work programming platform for simulating markets near wage equilibrium as well as work in computational game theory developing a meal prediction algorithm and user interface for Continuous Glucose Monitoring Systems that pairs a machine learning algorithm with models from behavioral economics. Summer 2014 Center For Hellenic Studies, Harvard University. Received an undergraduate research fellowship to study in residence at the Homer Multitext Seminar. Contributed work towards the publication of Iliad 12 in Harvard0s diplomatic Multitext edition of the Iliad, which is a project to combine multiple manuscripts of the Iliad and the marginal notes they contain into a set of XML files which are then parsed into a directed cyclic graph. Implemented an algorithm to perform optical character recognition on unusual 9th century Byzantine Greek ligatures that utilizes singular value decomposition and a support vector machine. Summer 2013 Boston University/Mass General Hospital Bionic Pancreas Trial, The Barton Center For Diabetes Education, Inc. While wearing the BU/Mass General Hospital investigational bionic pancreas discovered a garbage collection error in the production code that caused device to miss dosages. Code and Projects 2014-2015 Research, http://lumos.cs.trinity.edu/icibm). An interactive overview of my computational biology research that I presented as a first author poster at the 2014 International Conference on Intelligent Biology and Medicine. 2014 Toy Language, https://bitbucket.org/jluber/yeast). An interpreter for a Haskell like language with added F# style reference values and OO with Inheritance implemented in Haskell. 2012-2013 Older Projects, https://github.com/jacobluber. Old Scala and Haskell Projects, Recent C++ Projects Available Upon Request. Relevant Completed Coursework @ Trinity University. CS Honors Thesis, Linear Algebra, Compiler Engineering, Graphics, Game Design, Software Engineering, Thesis Readings, Analysis of Algorithms, Advanced Algorithms, Programming Languages, Artificial Intelligence, Special Topics in Computational Biology, Cloud Com- puting Seminar, Database Systems, Calculus,Theoretical Computer Science, Discrete Data Structures, Data Abstraction, Directed Studies in Economics, Directed Studies in Computer Science @ The Jackson Laboratory. 2015 Short Course on Mammalian Genetics Proficiencies Languages and Technologies. Python, C++, C, C#, R, Haskell, Scala, bash, MySQL, MIPS Assembly, LATEX, git, linux, gdb, Unity Conference Presentations, Posters, and Invited Talks 1 Jacob M. Luber, Joan Malcolm, Adam Lavertu, KB Choi, MA Hibbs, Joel H Graber, and Carol J Bult. Data mining diverse compendia of triple negative breast cancer samples for improved tumor subtyping [poster] *accepted. International Conference on Intelligent Systems For Molecular Biology, July 2016. Orlando, FL. 2 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. Predicting functional relationships in osteoblasts [talk] *accepted. Function SIG, July 2016. Orlando, FL. 3 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. Predicting functional relationships in osteoblasts [poster] *accepted. Function SIG, July 2016. Orlando, FL. 4 Jacob M. Luber. Improved prediction of mouse pathways related to bone mainte- nance through machine learning utilizing diverse genomic data [invited lightning talk]. Computational Systems for Integrative Genomics Workshop, April, 2016. Perelman School of Medicine, University of Pennsylvania. Philadelphia, PA. 5 Jacob M. Luber. Improved prediction of mouse pathways related to bone main- tenance through machine learning utilizing diverse genomic data [undergraduate thesis]. Trinity University CS Department Honors Undergraduate Thesis, March, 2016. Trinity University. San Antonio, TX. 6 Jacob M. Luber. Predicting pathways related to bone maintenence [talk]. Trinity University Biomath Seminar, October 2015. Trinity University. San Antonio, TX. 7 Jacob M. Luber and MA Hibbs. Methods for machine learning in functional genomics [talk]. Trinity University Math Majors Colloquium, September 2015. Trinity University. San Antonio, TX. 8 Jacob M. Luber, Joel Graber, and Carol J. Bult. Identifying genome signatures of drug response in patient derived xenografts (pdx): A machine learning approach [talk]. The Jackson Laboratory Summer Student Symposium, August 2015. The Jackson Laboratory. Bar Harbor, ME. 9 Jacob M. Luber, AX Jiang, and MA Hibbs. Discerning systematic bias in s. cerevisiae pathways using novel bayesian statistics problem structuring methods [poster]. Joint International Conference on Intelligent Systems For Molecular Biology and European Conference on Computational Biology Student Council Symposium, July 2015. Dublin, Ireland. 10 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hi- bbs. A context-specific machine learning method to predict novel osteoporosis related pathways [poster]. Joint International Conference on Intelligent Systems For Molecular Biology and European Conference on Computational Biology, July 2015. Dublin, Ireland. 11 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. Identification of osteoporosis-related genes using support vector machines [poster]. International Conference on Intelligent Biology and Medicine, December 2014. San Antonio, TX. 12 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hi- bbs. A machine learning method for prediction of osteoporosis-related genes [talk]. Gulf Coast Undergraduate Research Symposium, October 2014. Rice University. Houston, TX. 13 Jacob M. Luber. Support vector machine based learning techniques in functional genomics and computer vision [talk]. Computer Science Colloquium, November 2014. Trinity University. San Antonio, TX. 14 Jacob M. Luber. Machine learning techniques for optical character recognition of 9th century byzantine ligatures [talk]. Homer Multitext Seminar, July 2014. Harvard University Center For Hellenic Studies. Washington, DC. 15 Jacob M. Luber and MA Hibbs. Utilizing machine learning in computational biology and classics [talk]. Trinity University Summer Undergraduate Research Conference, July 2014. Trinity University. San Antonio, TX. 16 Jacob M. Luber. Software development for a bihormonal closed-loop bionic endocrine pancreas. Computer Science Colloquium, October 2013. Trinity University. San Antonio, TX..
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