Contact¶

Research focus¶

My research focuses on understanding 1) how information is represented in different brain regions, 2) how it gets transformed along various processing pathways, and 3) how these representational spaces are shared across brains. I use multivariate approaches to model between-subject similarity of representations, developing methods for aligning neural representational spaces across subjects in different brain regions, and building common model spaces that capture the essence of information represented in a brain region.

We developed a functional alignment method called hyperalignment that aligns the representational spaces across subjects and showed its general validity across experiments in the ventral temporal cortex (VT). I have since extended our method to other cortical systems across the whole brain, and developed a general framework to derive common models of representational spaces across various cognitive domains, and using connectivity profiles.

Here is a simple example showing hyperalignment in action & how to use it in PyMVPA: Hyperalignment example

Education¶

2008-2013:

Ph.D. in Cognitive Neuroscience at Dartmouth College, Hanover, NH, USA (Advisor: James V. Haxby)

2005-2007:

M.S. in Computer Science at Texas A&M University, College Station, TX, USA (Advisors: Bruce H. McCormick & Yoonsuck Choe)

2001-2005:

B.Tech in Mechanical Engineering at IIT Madras, Chennai, India

Publications¶