Aaditya Ramdas appointed Associate Professor

Aaditya makes his way to Stanford from Carnegie Mellon's Department of Statistics and Data Science, where he served a joint appointment with the Machine Learning Department in the School of Computer Science since 2018. After earning CMU MS and PhD degrees in statistics and machine learning, he completed a three-year postdoctoral appointment in EECS and statistics at UC Berkeley. Most recently, he's also spent time at Columbia and Georgia Tech, presenting a series of invited lectures on game-theoretic statistics.

Aaditya's research spans algorithms, theory, and applications of statistical inference and machine learning, with special focus on reproducibility in science and technology, active sequential decision-making, and assumption-light uncertainty quantification. He is the recipient of a 2024 Sloan Fellowship in Mathematics, the IMS Peter Gavin Hall Early Career Prize in 2023, a COPSS Emerging Leader Award and Bernoulli's New Researcher Award. Look for him in CoDa from September 1st!