I am a first-year Master's student in Electrical and Computer Engineering at the University of Texas at Austin, focusing on Computer Systems for AI and Machine Learning. I am currently working as a research assistant with Dr. Poulami Das, where I am working on improving the inter-token generation latency during LLM inferencing by tuning KV cache size using predictive ML methods.
Prior to this, I worked as an Applied ML Architect at NVIDIA, Bengaluru, working on GPU Architecture optimization, where I built ML-powered predictive models to project performance for NVIDIA's future products. I also helped build analytical models to debug inefficiencies in the current products, particularly for the gaming market (e.g NVIDIA DLSS). I also worked as a research assistant at H2Lab, University of Washington under Dr. Prithviraj Ammanabrolu, where I worked on deriving rewards from freeform linguistic feedback to train Large Language Models using RL.
My research interests lie in designing efficient computers used for running massive AI models. To this end, I am interested in using statistical methods, Reinforcement Learning and other optimization algorithms to design efficient end-to-end AI systems. I am also keenly interested in NLP, particularly Large Language Models, RLHF, and interactive systems.
I graduated from IIT Kharagpur in 2021 with a major in Electronics and Elec. Comm. and a minor in Computer Science. My bachelor thesis was on Training Generative Dialog Models using Reinforcement Learning with Learned Reward Systems, supervised by Dr. Pawan Goyal.
My hobbies include trekking, calisthenics, cooking (traditional Indian cuisines), and playing guitar. I also love reading scientific blogs related to astronomy and physiology.