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.
My academic background:
- ISTplus - Marie Skłodowska-Curie Fellow in the group of Prof. Gašper Tkačik at the Institute of Science and Technology Austria in 2019.
- Post-doctoral researcher in the group of Prof Raoul-Martin Memmesheimer at the University of Bonn, Germany in 2018.
- Post-doctoral researcher in the group of Prof Wulfram Gerstner at the École Polytechnique Fédérale de Lausanne, Switzerland from 2015 to 2018.
- PhD in Computational Neuroscience in the group of Prof Upinder S. Bhalla at the National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India, 2015.
- Master's in Physics, Tata Institute of Fundamental Research, Mumbai, India, 2009.
- Bachelor's in Electrical & Electronics Engineering, Indian Institute of Technology Madras, Chennai, India, 1996.
- Post-doc position on Causal eXplainable Reinforcement Learning at the University of Sheffield (deadline 18th March 2021): https://www.jobs.ac.uk/job/CEH708/research-associate-in-causal-explainable-reinforcement-learning-causalxrl , along with sister positions at the University of Vienna: https://ni.cs.univie.ac.at/ and INRIA, LIlle: https://jobs.inria.fr/public/classic/fr/offres/2020-03209.
- PhD position in cognitively-inspired reinforcement learning for robotics (deadline: 7th March 2021, international students are advised to apply even earlier as there is an extra panel): https://www.findaphd.com/phds/project/incorporating-self-and-world-models-in-neural-networks-for-flexible-robot-learning-and-control/?p130310.
- Another possible project (you'll need to apply for your own funding -- see here, or if selected by 28th March, I could nominate you for a Departmental scholarship competition). Email me in advance.