معرفی
Nicholas Cook is an Assistant Professor in the Department of Mathematics at Duke University. Currently on leave at the Berkeley SLMath Institute for the program on Probability and Statistics of Discrete Structures (Spring 2025). He will teach Math 690-40: Introduction to Random Matrix Theory in Fall 2025. His research focuses on high-dimensional probability, including random matrices, random graphs, large deviations, and universality phenomena, with connections to graph theory, additive combinatorics, free probability, and mathematical physics.
Background: Cook earned his PhD in 2016 from UCLA under Terence Tao. He was a Stein Fellow at Stanford University's Statistics Department and held NSF postdoctoral positions at Stanford and UCLA. His academic journey includes affiliations with Amir Dembo and Jun Yin as postdoctoral sponsors.
Research interests span broad areas such as concentration of measure, universality in random structures, and applications in numerical analysis and statistics. His recent work emphasizes large deviation principles for eigenvalues, universality in random matrix ensembles, and combinatorial problems in graph theory. Articles published since 2018 reflect a deep engagement with spectral properties of random structures and their probabilistic behaviors.
Teaching and academic service: Currently on research leave, Cook has taught advanced courses in probability and random matrix theory. His academic contributions are supported by NSF grants, though specific grant details are not provided here.
