I completed my undergraduate degree in Electrical Engineering from Indian Institute of Technology Roorkee. After that, I worked as a Research Fellow in Adobe Research for two years. There, I worked on problems in the area of sequence modeling and human decision making. I have now developed a research interest in Reinforcement Learning (RL). I am motivated by the prospect that RL can serve as a general framework for solving intelligent decision-making problems across domains. More specifically, I am interested in addressing research challenges of partial observability, sparse rewards, sample inefficiency, multiple goals and multi-agent dynamics. In general, I like to think and read about ways to advance machine cognition. The Google AI residency program has provided me with the right environment and mentorship to develop my research skills. I am collaborating with the Robotics NY team to improve sample efficiency of RL algorithms for legged locomotion task. My mentors welcome new ideas from me and guide me to the right direction for further exploration. Google’s infrastructure makes trying out experiments very easy. It is exciting to tackle challenges in deploying policies on a real robot. I am enjoying this learning experience. Outside work, I love creating art, reading and exploring the city.