Sam Daulton

Research Scientist - Core Data Science

I am a research scientist in the Core Data Science team’s Adaptive Experimentation group. My research focuses on developing methods for contextual bandit optimization, reinforcement learning, and Bayesian optimization. Prior to joining Facebook, I was at Harvard University, where my work focused on developing robust and efficient transfer learning methods to advance towards disseminating reinforcement learning to high-stakes human applications.


Bayesian optimization, contextual bandits, reinforcement learning, transfer learning

Related Links

Personal website

Latest Publications

NeurIPS - December 7, 2020

BOTORCH: A Framework for Efficient Monte-Carlo Bayesian Optimization

Max Balandat, Brian Karrer, Daniel Jiang, Sam Daulton, Ben Letham, Andrew Gordon Wilson, Eytan Bakshy

Workshop on Safety and Robustness in Decision Making at NeurIPS - December 2, 2019

Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints

Sam Daulton, Shaun Singh, Vashist Avadhanula, Drew Dimmery, Eytan Bakshy