Aditya Grover

Email: adityag at

I am a fourth-year Ph.D candidate in Computer Science at Stanford University, affiliated with the Artificial Intelligence Laboratory and the Statistical Machine Learning Group. My advisor is Stefano Ermon.

I am interested in developing algorithms for efficient learning and inference in probabilistic models. A large part of my research focus in this direction entails the design and analysis of suitable learning objectives (AAAI 2018), improving algorithms for stochastic optimization via approximate inference and uncertainty quantification (AISTATS 2018), and grounding such learning frameworks for applications across machine learning e.g., multiagent reinforcement learning, compressed sensing, and constraint satisfaction (ICML 2018, NIPS 2018).

My research is supported by a Microsoft Research PhD Fellowship in machine learning and a Stanford Data Science Scholarship. In the course of my Ph.D, I have spent two summers interning at OpenAI (2017) and MSR, Redmond (2018). Before joining Stanford, I obtained my bachelors in Computer Science and Engineering from IIT Delhi in 2015.


Conference Publications

[* denotes equal contribution]