Research Interests:

Computational Learning:
Efficient approaches for solving machine learning tasks: Inference, classification, data mining and optimal decisions using sparse,noisy data. Much of my work is geared to construct scientific hypotheses in biological/medical research domains using probabilistic graphical models

Biological/Medical Research:
My computational work is motivated by problems from these domains. Specifically, In the last few years I have focused on improving the understanding of regulatory mechanisms in the living cell.  Much of my initial work was concentrated on transcription regulation. Since I joined UofT, I have been working to unravel the code underlying alternative splicing. This is a totally uncharted area of research with direct impact on our understanding of human genetic code and diseases. I find this area of research most inspiring in both the biological and computational aspects of it.