Adith Swaminathan is a research scientist in the Machine Learning and Inference Research team at Netflix. He studies machine learning to improve decision-making for user-interactive systems, including recommender systems, LLM-augmented agents, interactive games and cloud computing systems. He received a PhD from Cornell University in 2017 and was a researcher at Microsoft Research Redmond from 2017-2024.

Sharon Li is an Associate Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. Her research focuses on algorithmic and theoretical foundations of reliable machine learning, addressing challenges in both model development and deployment in the open world. Previously she was a postdoc researcher in the Computer Science department at Stanford University. She completed her Ph.D. from Cornell University, advised by John E. Hopcroft. She serves as the Program Chair for ICML 2026. She was the recipient of Alfred P. Sloan Fellowship (2025), NSF CAREER Award (2023), MIT Innovators Under 35 Award (2023), AFOSR Young Investigator Award (2022), Forbes 30under30 in Science (2020), and multiple faculty research awards from Google, Meta, and Amazon. She was named the “Innovator of the Year 2023” by MIT Technology Review. Her works have won the Outstanding Paper Award at NeurIPS 2022 and ICLR 2022.