معرفی
Vadim Sokolov is an Associate Professor in the Department of Systems Engineering and Operations Research at George Mason University (GMU), with affiliate status in the College of Engineering and Computing (CEIE). His research focuses on developing robust methodologies for large-scale systems analysis, combining agent-based modeling, Bayesian statistical techniques, and computational experimentation. He co-developed Polaris, an open-source mobility simulator widely used in transportation network analysis by government entities.
Previously, Sokolov served as a Principal Computational Scientist at Argonne National Laboratory, a Fellow at the University of Chicago's Computation Institute, and a Lecturer at the University of Chicago. He holds a Ph.D. in Computational Mathematics from Northern Illinois University.
His research interests span agent-based modeling, Bayesian analysis, transportation systems, and computational software development. Notable contributions include work on stochastic computer models, deep learning applications in traffic flow prediction, and quantum Bayesian computation. He has published in top-tier journals such as the Annals of Applied Statistics and Transportation Research Part C.
Though no awards are explicitly listed, his extensive publications and industry collaborations highlight his impactful work in computational systems and transportation analysis.
