Speakers:

• Adrian Bowman, University of Glasgow - Modelling Surface Anatomy: Lots of Data, Lots of Structure

• Partha Pratim Majumdar, National Institute of Biomedical Genomics - Analyzing Genome-Scale Data on Cancer: Computational and Statistical Challenges

• Kanti Mardia, University of Leeds - Shape Manifold and Curves in the Context of Big Data

• David van Dyk, Imperial College London - Big Data and Complex Modeling Challenges in Astronomy and Solar Physics

• Jonathan Marchini, University of Oxford - Statistical Methods for Genetic Studies of Multiple Phenotypes in Related Samples

• Christopher Yau, University of Oxford - The Hamming Ball Sampler

• Indranil Mukhopadhyay, Indian Statistical Institute - Tight Clustering for Large Datasets

• Guido Sanguinetti, University of Edinburgh - Machine Learning for Epigenetics: Some Initial Results

• Arief Gusnanto, University of Leeds - Statistical Analysis of Copy Number Alterations Using Next-Generation Sequence Data

• Darren Wilkinson, Newcastle University - Stochastic Modelling of Genome-Wide Robotic Screens for Genetic Interaction in Yeast

• Dirk Husmeier, University of Glasgow - Sparse Models for Genetic-Antigenic Associations

• Sanghamitra Bandopadhyay, Indian Statistical Institute - Locality Sensitive Hashing for Sequence Similarity Search: Applications in Big Data

• Vincent Macaulay & Alasdair Mcintosh, University of Glasgow - Comparing Competing Demographic Models for Big Genomic Datasets

• Sujit Sahu, University of Southampton - On Generating a Flexible Class of Anisotropic Spatial Models Using Gaussian Predictive Processes

• Ludger Evers, University of Glasgow - Functional Distributional Clustering with an Application to the Spatial Partitioning of Traffic Networks

• Natalia Bochkina, University of Edinburgh - Selection of the Regularization Parameter in Graphical Models Using a Priori Knowledge of Network Structure

• Saumyadipta Pyne, CRRao AIMSCS - Computational Biosecurity via High-Dimensional Modeling of Immunophenotypic Diversity in Populations

• Arnab K. Laha, Indian Institute of Management - Statistical Challenges with Big Data in Management Science

• Martin Hendry, University of Glasgow - 2020 Vision: Exploring the Cosmos with the Next Generation of Astronomical Telescopes

• John Moriarty, University of Manchester - Bayesian Inference on Mixtures of Ornstein-Uhlenbeck Processes for Modelling Electricity Spot Prices

• Sandosh Padmanabhan, University of Glasgow - Challenges in Real-Life Healthcare Data Analysis

• Paul Fearnhead, Lancaster University - Scaling Changepoint Detection to Big Data

• Koel Das, Indian Institute of Science Education and Research - Large Scale Data Analysis in Cognitive Neuroscience

• Marian Scott, University of Glasgow - The Environmental 'Data Deluge' and Statistical Challenges it Presents

• John Aston, University of Cambridge - Object Data Analysis for One or More Dimensional Signals

• Surajit Ray, University of Glasgow - Spatially Correlated Functional Data Analysis

• Debasis Kundu, Indian Institute of Technology - Multivariate Geometric Skew-Normal Distribution

• Yogesh Simmhan, Indian Institute of Science - Big Data Platforms and Tools for Smart Infrastructure

• Patrick Wolfe, University College London - Understanding the Behaviour of Large Networks

• Sumeetpal Singh, Cambridge University - Particle Gibbs for State-Space Models with Long Data Sequence