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Simon Mak is an Assistant Professor in the Department of Statistical Science at Duke University, where he has been serving since 2019. His research interests include Bayesian inference, jet quenching in heavy-ion collisions, and the development of data-driven surrogate models for engines. Mak is also involved with the Duke Institute for Brain Sciences, signifying his interdisciplinary approach to research. He has published several articles in esteemed journals such as Physical Review C, contributing to the understanding of momentum conservation in small systems and the dynamics of jet transport parameters in quark-gluon plasma. His educational background includes a Ph.D. and M.S. from the Georgia Institute of Technology, and a B.S. from Simon Fraser University. Mak actively collaborates on various grants and projects aimed at advancing statistical methodologies in scientific discovery and predictive modeling.
Duke University • Durham, NC
Conducting research and teaching in the Department of Statistical Science.
Department of Biomedical Engineering (MS program)