I am currently, a Co-Founder at Aliveo AI. We are building a data copilot for marketing and growth teams to accelerate data-driven decision-making. In my past role, I was a Senior Staff Software Engineer in LinkedIn's AI team, primarily focusing on Responsible AI, encompassing challenging problems in Fairness, Explainability, and Privacy. I led several efforts that can be applied to different product applications towards making LinkedIn a responsible and equitable platform.Through the years, I have worked on a variety of problems and on various product applications. My focus has ranged from developing prediction models for complex recommender systems powering News Feed Ranking and People You May Know (PYMK) to extreme large-scale optimization problems trying to solve complex matching and allocation problems. I've been the chief architect and designer for the AutoML library used internally by various teams such as Feed, Notifications, Ads and PYMK. I've also worked towards developing accurate causal estimates in the presense of network interference. Most of my work has been published in top ML/AI conferences such as NeurIPS, ICML, KDD (Research and Applied Track), WWW, etc. Before joining LinkedIn, I finished my Ph.D. in the Department of Statistics at Stanford University advised by Prof. Art Owen. My dissertation was on Quasi-Monte Carlo Methods in Non-Cubical Spaces. Prior to the doctoral program, I earned my B. Stat (Hons) and M.Stat (Specializing in Mathematical Statistics and Probability) from Indian Statistical Institute, Kolkata.