Daniel Siefman is an assistant professor in the Nuclear Engineering Department at UC Berkeley. His research interests include critical and subcritical experiments and methods, nuclear data validation and adjustment, computational methods in radiation transport, neutron noise, reactor dosimetry, design optimization and safety analysis of nuclear reactors with machine learning, and nuclear power plant decommissioning. Daniel received a bachelor’s degree in Nuclear Engineering from the University of Florida and a PhD in Nuclear Engineering from EPFL in 2019. From 2019 to 2023, he was a staff scientist in the Nuclear Criticality Safety Division at Lawrence Livermore National Laboratory supporting R&D efforts in integral experiments, nuclear data validation, radiation transport, neutron noise, and diagnostics for nuclear emergency response.