Fan Wei

Fan Wei is an Assistant Professor of Mathematics at Duke University, affiliated with the Department of Mathematics. His research focuses on extremal combinatorics, probabilistic combinatorics, and applications of combinatorics to computer science. He is particularly interested in using tools from probability, analysis, and algebra to analyze large networks and other combinatorial objects. Wei completed his PhD in mathematics in 2019 from Stanford University and was a post-doctoral member at the Institute for Advanced Study. He is currently seeking motivated students to join his research or reading group.

Fan Wei is a mathematician specializing in Analysis, Combinatorics, and Probability. Their research focuses on graph theory, combinatorial optimization, and probabilistic methods, with applications in machine learning and theoretical computer science. Wei's work includes studies on clique detection, graph partitioning, and density measures for language generation. They have explored topics such as smoothed analysis, property testing, and extremal graph theory, contributing to the understanding of structural properties in graphs and their algorithmic implications. Their research also addresses fundamental questions in combinatorics, such as the inducibility of random graphs and the asymptotic behavior of graph densities.