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title
Samuel (Sam) Daulton
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Personal website
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Samuel (Sam) Daulton
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2026-02-20 21:00:09
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Samuel (Sam) Daulton I am a research scientist at Meta on the Central Applied Science team. Within Core Data Science, I work in the Adaptive Experimentation research group. My research focuses on methods for principled, sample-efficient optimization including Bayesian optimization and transfer learning. I am a co-creator of BoTorch ---an open source library for Bayesian optimization research. I am particularly interested in practical methods for principled exploration (using probablistic models) that are robust across applied problems and depend on few, if any, hyperparameters. Furthermore, I aim to democratize such methods by open sourcing reproducible code. I completed my PhD at the University of Oxford where I worked with Michael Osborne, and I worked with Finale Doshi-Velez at Harvard University on efficient and robust methods for transfer learning during my master's degree. In my free time, it's a safe bet that I'm climbing, skiing, running, scuba diving, or sch...
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