About me!
I am a 2nd year Computer Science PhD student at Massachusetts Amherst where I am advised by Dr. Yair Zick. My research interests are in Trustworthy Machine Learning, Reinforcement Learning, and Optimization. My research focus is on explanation frameworks that are a) Fair - the quality of the explanations does not degrade for minority groups due to insufficient data, b) Robust - the explanations generated by the frameworks are robust to small perturbations in the data, c) Private - they do not leak private information of users and thus have strong privacy guarantees and d) Practical - they are computationally inexpensive and can be axiomatically characterized.
I am also interested in developing practical RL algorithms that leverage human feedback and expert knowledge to efficiently solve real-world sequential decision-making problems with limited data.
Before joining UMass Amherst, I worked as a graduate research assistant at the University of New Hampshire for 1.5 years. During this period, I was fortunate to be advised by Dr. Marek Petrik on several research problems in Reinforcement Learning, including data poisoning attacks on policy evaluation algorithms, handling model uncertainty in offline RL, and variance reduction techniques for risk-estimators in RL. I completed my Masters in Computer Science at the University of Massachusetts Amherst in 2020 and obtained my BTech in Electronics and Communication Engineering from NIT Durgapur in 2016. I also worked as a Software Engineer at Directi Web Technologies and Flipkart from 2016 to 2018.
You can find my updated resume here.
You can contact me by email.