Tentative Schedule:
6:30pm: Pizza + Beer networking
7:00pm: TBD with Data Scientist at Dataiku
7:30pm: A Bayesian Approach To Model Overlapping Objects Available As Distance Data with Sandhya Prabhakaran, Researc Fellow at Memorial Sloan Kettering Cancer Centre

Talk Abstracts:
A Bayesian Approach To Model Overlapping Objects Available As Distance Data with Sandhya Prabhakaran, Researc Fellow at Memorial Sloan Kettering Cancer Centre:
Traditional clustering methods often partition objects into mutually exclusive clusters - however, it's more realistic that objects may belong to multiple, overlapping clusters. When healthcare data is available in pairwise distances -- such as in genomic string alignments, protein contact maps, or pairwise patient similarities - there is no probabilistic clustering model that allows such overlap, & solutions for these types of models are often noisy & heavily biased. Therefore, it would be advantageous to have a model which caters to clustering distance data directly.

In this talk, we'll address this problem & introduce a Probabilistic model for Overlapping Clustering on Distance data (POCD) that gives objects the freedom to belong to one or more clusters at the same time. Since POCD is a probabilistic model, on output we obtain samples from a distribution over partitions & use an Indian Buffet Process (IBP) beforehand to remove the need to pre-emptively fix the number of overlapping clusters. We will demonstrate the benefits of working with distances directly & the utility of POCD in both simulated as well as real world distance data of neonatal patients & HIV1 protease inhibitor contact maps.

(This is joint work with Julia E. Vogt (Department of Computer Science, ETH, Switzerland & Swiss Institute of Bioinformatics (SIB), Basel, Switzerland))

Speaker bios:
Sandhya has been a Research Fellow at Memorial Sloan Kettering Cancer Centre beginning in December of 2016. Before that, from October 2014, she was a Research Scientist at the same lab at Columbia University in the City of New York. Sandhya received her Ph.D degree from the Department of Mathematics & Computer Science, University of Basel, Switzerland & her Masters in Intelligent Systems (Robotics) from University of Edinburgh, Scotland. My research deals with developing statistical theory & inference models, particularly to problems in Cancer Biology. Prior to academics, she was an Assembler programmer working with the Mainframe Operating System (z/OS) at IBM Software Laboratories, Bangalore & has developed Mainframe applications at UST Global, Kerala. She is an avid hiker & distance runner & has completed 4 of the 6 World Marathon Majors. Webpage: www.sandhyaprabhakaran.com
Twitter: @sandhya212