I'm interested in discovering and learning about the world around (and in) us, irrespective of discipline. My primary research interests are in the areas of learning in the brain and in artificial neural networks. I endeavour to figure out how the brain learns (see my publications and related code), using theoretical and simulational tools from computational neuroscience, control theory, machine learning and statistical physics. Recently, I've used: adaptive control theory to derive biologically plausible learning rules for connection weights in spiking neural networks especially for motor control; and memory-augmented neural networks to solve cognitive tasks using reinforcement learning. If you have similar (or complementary!) interests, feel free to contact me.

I'm a Lecturer in the Machine Learning Group at the Department of Computer Science, in the University of Sheffield, UK. I'll be advertising for a PhD position in my group shortly. Stay tuned, or write to me.

Earlier, I was a post-doctoral researcher in the groups of Prof. Gašper Tkačik at the Institute of Science and Technology, Austria, Prof Raoul-Martin Memmesheimer at the University of Bonn, Germany, and Prof Wulfram Gerstner at the École Polytechnique Fédérale de Lausanne, Switzerland. I have a background in Computational Neuroscience (PhD - National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India with Prof Upinder S. Bhalla), Physics (Master's - Tata Institute of Fundamental Research, Mumbai, India) and Electrical & Electronics Engineering (Bachelor's - Indian Institute of Technology Madras, Chennai, India).

Check out my publications and related code, code for general-purpose neural simulation, and tutorials.