Table of Contents Inaugural Lecture 7 High Dimensional Clustering, Variable Selection and Social Networks 7 Jayanta K. Ghosh Plenary Talk I Statistical Aspects of SNP – Gene Expression Studies 8 Andreas Ziegler Plenary Talk II Statistical Methods for Biomedical Research on Diagnostic Ultrasound 8 Douglas Simpson Invited Talks 9 Bayesian Methods for Clustering Functional Data 10 Subhashis Ghoshal Bayesian Average Error Based Approach to Sample Size Calculations for Hypothesis Testing 11 Eric Reyes and Sujit K. Ghosh Bayesian Analysis of Life‐data under Competing Risks 12 Ananda Sen A Distribution Theory for Predictive‐R2 in High‐dimensional Models and its Implications for Genome‐wide Association Studies 12 Nilanjan Chatterjee Comparison of Methods for Unsupervised Learning Methods – an Applied Study Using Proteomic Data From Colon Cancer and Simulations 13 Nairanjana Dasgupta, Yibing Oliver Chen, Rashmita Bas and Sayed S. Daoud Incorporating Auxiliary Information for Improved Prediction in High Dimensional Datasets: An Ensemble of Shrinkage Approaches 13 Bhramar Mukherjee Unconstrained Bayesian Model Selection on Inverse Correlation Matrices with Application to Sparse Networks 14 Nitai D. Mukhopadhyay and Sarat C. Dass Analysis of Sabine River Flow Data Using Semiparametric Spline Modeling 15 Soutir Bandyopadhyay 1 Adaptive Density Regression with Gaussian Process Priors 15 Surya T. Tokdar Independent Component Analysis for Dimension Reduction Classification: Hough Transform and CASH Algorithm 16 Asis K. Chattopadhyay Predicting the Extent of Uniqueness of a Fingerprint Match 16 Sarat C. Dass Statistical Models for Biometric Authentication 17 Sinjini Mitra Robust ER‐fMRI Designs under a Nonlinear Model 17 Dibyen Majumdar Statistical Planning and Inference in the Data‐centric World: Applications and Challenges 18 Subir Ghosh Constrained Multi‐objective Designs for Functional MRI Experiments via a Modified NSGA‐II 18 Abhyuday Mandal Bayesian Learning of Material Density Structure and Blurring Function by Inverting Images Taken with Electron Microscopy Techniques 19 Dalia Chakrabarty The Discrete Charm of Convex Optimization: from Shape‐constrained Density Estimation to Empirical Bayes Decision Rules 20 Ivan Mizera The use of Topographic Mapping in Visualisation and Classification: Application to Finding Planets around Other Stars 20 Somak Raychaudhury Bootstrapping for Significance in Clustering 21 Ranjan Maitra Modeling Climate Characteristics Using Small Area Methodology 21 Snigdhansu Chatterjee Functional Factor Analysis for Periodic Remote Sensing Data 22 Chong Liu, Surajit Ray, Giles Hooker and Mark Friedl 2 Recombination Detection and its use in Inferring the Recent Human Evolutionary History Marta Melé, Marc Pybus, Asif Javed, Laxmi Parida, Francesc Calafell and 22 Jaume Bertranpetit High Resolution Mapping of DNA Methylation 23 Karin S. Dorman, X. Yin and X. Wang Pathway Association Tests Using Reduced Gene Subsets for Genome‐wide Association Studies 24 Jingyuan Zhao, Simone Gupta, Mark Seielstad, Jianjun Liu and Anbupalam Thalamuthu An Investigation into Market Evolution and Consumer Dynamics in an Online Art Market: a Case of Modern Indian Art 25 Mayukh Dass Scale Equivariant Estimators for Diffusion Models 25 L. Ramprasath Correlations in Financial Time‐series: An Econophysicist's Perspective 26 Anirban Chakraborti Logic Trees for Multilevel Data: Application to Cancer Care 26 Mousumi Banerjee Predictive Problems in High‐dimensional Data: Some Examples 27 Madhuchhanda Bhattacharjee Probability Machines and Risk Modeling 28 Abhijit Dasgupta and James Malley Contributed Papers 29 A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case‐Control Studies 31 Dhiman Bhadra, Michael J.Daniels, Sungduk Kim, Malay Ghosh and Bhramar Mukherjee Bayesian Estimation of Reliability Measures for a Family of Lifetime Distributions Using Masked System Lifetime Data 32 Sanjeev K. Tomer and Ashok K. Singh Diffusive Limits for Adaptive MCMC 32 Gopal K. Basak and Arunangshu Biswas 3 Using Centered and Non‐centered Algorithms for Simulating S&P Share Index Data 33 Mahsa Ashouri Statistical Methods to Identify Clonal Variations Present in Tumour 33 Sayar Karmakar, M.Mukherjee, A. Basu and A. Ghosh Admixture Time Estimation Using Random Genetic Drift Model 34 Shrijita Bhattacharya, A. Basu and A. Ghosh Estimating Relationship between Random Individuals from their Genome Sequence 36 Soudeep Deb A Deterministic Model for HIV Infection Incorporating Identification Rate in a Heterosexual Population: Mathematical Analysis 36 Manindra Kumar Srivastava and Purnima Singh Genome‐wide Association Studies for Bivariate Sparse Longitudinal Data 37 Kiranmoy Das, Jiahan Li, Guifang Fu, Zhong Wang and Rongling Wu The Interactions among Candidate Genes May Lead to Severity of Mental Disorders 38 Basant K. Tiwary Estimating Headrooms of Indian ADRs‐ An Application of Nonlinear Filtering Technique 38 Kaushik Bhattacharjee Replacement Analysis Using Fuzzy Linguistic Theory 40 Prakash R.Chavan, V.H.Bajaj and J.G.Haridas Mammogram Segmentation by Near Set Approach and Mass Lesions Classification with Rough Neural Network 40 Vibha Bafna Bora, A.G. Kothari and A.G.Keskar An Application of Data Mining Tools for the Study of Shipping Safety 41 Aby Subhash and Kelangath S On Univariate Process Capability Indices for Unilateral Tolerances 42 Moutushi Chatterjee and Ashis Kumar Chakraborty Functional Data Analytic Methodology for PBPK Models 42 Siddhartha Mandal 4 Early Marriage and the Length of First Birth Interval in India 43 Shilpi Tanti and K.K. Singh Fitting a Mixture of Conway‐Maxwell‐Poisson Distributions to Count Data 44 Pragya Sur, Paromita Dubey, Smarajit Bose and Galit Shmueli New Stein’s Estimators of Regression Coefficients in Replicated Measurement Error Model 44 Sukhbir Singh, Kanchan Jain And Suresh Sharma Copula Based Dependence Structures among Maternal Variables 45 Ranjana Gogoi and Navajyoti Tamuli Statistics in Industry 47 And the Two Twains Shall Meet 49 N. R. Srinivasa Raghavan "What's in a Name?" 49 K Vijay Kumar Reliability, Availability, and Productivity for Wind Turbines 50 Abhinanda Sarkar Tracking Consumer Segments 50 Arabinda Ghosh Managing Expectations: Statistics in Risk Management Karra Sanghamitra 51 Posters 53 An Optimum Multivariate Stratified Sampling Design with Travel Cost in Presence of Non‐Response: A Goal Programming Approach 55 Saman Khowaja, Shazia Ghufran and M. J. Ahsan Multiple Comparison Procedure for Comparing Several Exponential Populations with Control in Terms of Location Parameters Under Heteroscedasticity 55 Vishal Maurya, Amar Nath Gill and Parminder Singh Optimum All Order Neighbor Balanced μ‐Resolvable BIB Designs 56 Anurup Majumder and Aatish Kumar Sahu 5 Simultaneous Prediction Intervals for Comparing Several Treatments with More than One Control 57 Sukhbir Singh, Anju Goyal and Vishal Maurya Some Probability Models for Waiting Time to First Conception 58 R.C.Yadava, S.K. Singh, Anup Kumar and U Srivastava On Comparing the Performance of Senior and Young Cricketers in Indian Premier League 58 Hemanta Saikia and Dibyojyoti Bhattacharjee Almost Unbiased Ratio and Product Type Exponential Estimators 59 Rohini Yadav, Lakshmi N. Upadhyaya, Housila P. Singh and S. Chatterjee Bayesian Estimation and Prediction of Generalized Inverted Exponential Distribution 60 Sanku Dey, Tanujit Dey and Debasis Kundu On the Bayes Estimators of the Parameters of Non‐Zero Inflated Generalized Power Series Distributions 60 Peer Bilal Ahmad Relations for Marginal and Joint Moment Generating Functions of Generalized Exponential Distribution Based on Lower Generalized Order Statistics and 61 Characterization R.U. Khan, and Benazir Zia On Exact Non‐Parametric Alternative Tests in Two‐Way Layout 61 Maidapwad S. L. and Sananse S.L A Test for the Significance of Treatment Effect in a Mixture Population 61 Bikram Karmakar, Kushal Kumar Dey and Kumaresh Dhara Valedictory Address Pranab K. Sen 62 6 Inaugural Lecture High Dimensional Clustering, Variable Selection and Social Networks Jayanta K. Ghosh Purdue University, West Lafayette, IN, USA and Indian Statistical Institute, India At various times in the recent past, 2005 onwards, I have discussed the relevance of Bayesian Nonparametrics (specifically, Dirichlet mixtures of the normal) for handling non‐unique clustering in high dimensional problems, for example the problem given to ISI by Professor Madhab Gadgil. The data had about 50,000 superpixels, each based on 1000 pixels of satellite pictures on the Western Ghat area, in four bands. In such problems, k‐means clustering does not provide unique results, results depend on starting points. Dirichlet mixtures can be shown to be very close to k means clustering, and the NP Bayes approach can assign probabilities to the different clusterings that come out as MCMC outputs. I also discussed a notion of central clustering and a neighborhood of it such that all satisfactory clusterings will lie there. I have developed a metric between clusterings with help from young colleagues, for example Tapas Samanta, Kajal Dihidar etc. Later I had discussions with Sourabh Bhattacharya and Sabyasachi Mukhopadhyay. In Kulis and Jordan (2011), they achieve remarkable progress on these problems. Further major insight and powerful new results and methods have been obtained recently by Bogdan et. al. (2011). They prove a deep theorem connecting k means clustering with Dirichlet mixtures, throwing major