Benjamin Nachman

Benjamin Nachman leads a scientific machine learning group that is developing, adapting, and deploying statistical learning / machine learning solutions for particle, nuclear, and astrophysics. Key areas include surrogate modeling (e.g. with generative AI), simulation-based inference, and anomaly detection. He received his Ph.D. in physics with a Ph.D. minor in statistics from Stanford University in 2016. In 2022, Nachman received a DOE Early Career Award for developing automated, HPC-compatible anomaly detection methods. He is also on the executive committee of the American Physical Society’s Group on Data Science.