
This workshop is jointly funded by the:
Engineering and Physical Sciences Research Council (EPSRC), U.K., and
Indian Department of Science and Technology (DST)
through the
EPSRC-DST Indo-UK Initiative in applied mathematics.
Driven by the statistical challenges of "Big Data" analysis in modern scientific applications, the goal of this workshop is to shape future directions in the area of big data modelling and
analysis, consolidating the strengths of statisticians from the UK and India as well as training future
researchers. Due to increases in
computational power, statistical techniques are now used to fit increasingly complex models to increasingly large
datasets arising from a variety of fields, ranging from medical imaging, genomic
and genetic high-throughput assays, to remote sensing, power grids, and social networks.
In recent years, there has been a
huge upsurge in data collection in genomics and medicine- vast databases have come into existence for
recording every piece of biological information ever collected about individual locations in the human
genome (as well as many other species). At the same time, there have been massive improvements in the
scope and accuracy of measuring instruments, that have led to a rich record of climate and environmental
exposure data over a wide geographical area. However, for all this information to be of actual clinical use-
for example, in risk prediction for cancer or a variety of other diseases and genetic conditions- there need
to be the development of statistical models and methods that are appropriate to handle the complexity and
diversity of the types of data as well as be computationally feasible to implement in real time.
The
new applications pose challenges in computation, estimation, and especially in statistically sound inference
techniques for high dimensional data.
Statistical techniques developed for analysing big data arising from different application areas
are quite diverse, yet the underlying challenges are often very similar; but there are few venues where statisticians working on different topic areas get a chance to exchange their ideas and expertise in
sufficient depth.
In the workshop, we will focus on bringing together ideas on big data analysis challenges from three major application areas:
- Genetics, Genomics and Biomedical Applications
- Environmental issues
- Energy, infrastructure, and emerging technologies
Building cross-connections through the workshop, through the exchange of statistical and
mathematical ideas, techniques and tools, the end-goal would be
to consolidate these into a novel synthesis of methodologies leading to new breakthroughs in
solving scientific problems from a multi-pronged and multi-disciplinary statistical perspective.
Detailed information on the location, accommodation and travel is available at the official
ICMS workshop page.
Confirmed invited speakers (from the U. K.) as of April 28, 2015 include:
John Aston | University of Cambridge |
Natalia Bochkina | University of Edinburgh |
Adrian Bowman | University of Glasgow |
Ludger Evers | University of Glasgow |
Paul Fearnhead | Lancaster University |
Arief Gusnanto | University of Leeds |
Dirk Husmeier | University of Glasgow |
Vincent Macaulay | University of Glasgow |
Jonathan Marchini | University of Oxford |
Kanti Mardia | University of Leeds |
John Moriarty | University of Manchester |
Sandosh Padmanabhan | University of Glasgow |
Surajit Ray | University of Glasgow |
Guido Sanguinetti | University of Edinburgh |
Sujit Sahu | University of Southampton |
Marian Scott | University of Glasgow |
Sumeetpal Singh | University of Cambridge |
Darren Wilkinson | Newcastle University |
Susan Waldron | University of Glasgow |
Patrick Wolfe | University College, London |
David Van Dyk | Imperial College, London |
Christopher Yau | University of Oxford |
Confirmed invited speakers (from India) include:
Sanghamitra Bandopadhyay | Indian Statistical Institute, Kolkata |
Koel Das | Indian Institute of Science Education and Research, Kolkata |
Debasis Kundu | Indian Institute of Technology, Kanpur |
Arnab K. Laha | Indian Institute of Management, Ahmedabad |
Partha Pratim Majumdar | The National Institute of Biomedical Genomics |
Indranil Mukhopadhyay | Indian Statistical Institute, Kolkata |
Saumyadipta Pyne | C. R. Rao institute, Hyderabad |
Yogesh Simmhan | Indian Institute of Science, Bangalore |