University of Cambridge, UK
Indian Institute of Science, Bangalore
As an electronics and computer engineering undergraduate at the University of York, I was interested in machine intelligence, consequently leading to my work on optimizing hardware?software co?design of complicated control systems like fighter planes, space shuttles, etc. Inspired by classical work in artificial intelligence, I began to consider computations in biological systems, especially within and between neurons. As a result of this interest my undergraduate thesis focused on short?term synaptic plasticity in pyramidal neurons in the hippocampus. During the summers I worked on optimizing linear algebra libraries for statistical parametric modeling – a widely used tool in neuroimaging. I continued at the University of York and read for an MSc degree in theoretical computer science. During this time I primarily studied fear-conditioning circuits in the auditory pathway. I then joined the Max Planck Institute in Tübingen, Germany for a second MS level course in neuroscience to supplement my understanding of the nervous system. At Tübingen, I had the opportunity to learn theoretical and experimental techniques on both rodents and non?human primates working in the intersection of neurophysiology, machine learning, optimization and statistical physics. I returned back to England in 2007 to start a PhD in Cambridge, working on the trade?offs between information encoding and energy consumption in single neurons. On completion of my PhD, I joined the Indian Institute of Science in Bangalore as a Wellcome Trust Fellow.
Presently, I am interested in the analytical and numerical analysis of biological systems to understand the physics of computation. In particular, my work has focused on applying mathematical analysis when possible and numerical simulations when necessary to understand how information is encoded in single neurons and the flow of information through networks of neurons.