Aditi Raghunathan

Aditi is an Assistant Professor in the Computer Science Department at Carnegie Mellon University. She is also affiliated with the Machine Learning Department.

Aditi works broadly in machine learning and her goal is to make machine learning more reliable and robust. Her work spans both theory and practice, and leverages tools and concepts from statistics, convex optimization, and algorithms to improve the robustness of modern systems based on deep learning.

Aditi’s group research is generously supported by an AI2050 Early Career Fellowship from Schmidt Futures, Apple, Google, and Open Philanthropy.

Until recently, she was a postdoc at Berkeley AI Research. Aditi received her PhD from Stanford University in 2021 where she was fortunate to be advised by Percy Liang. Her thesis won the Arthur Samuel Best Thesis award at Stanford. Previously, she obtained her BTech in Computer Science from IIT Madras in 2016.