Research Area : Numerical Linear Algebra, Random Matrix Theory
My research interest lies on the intersection of random matrix theory, numerical linear algebra and classical matrix theory. I work with pure linear algebra and Lie theory and to derive new algorithms in numerical linear algebra such as matrix factorizations. The other way around, I have used numerical algorithms to derive theoretical results such as random matrix eigenvalue statistics via Fredholm determinantal representations. Another part of my research explores new connections between discrete and continuous random matrix theory, for example, ghost beta random matrices or noninteger sized random matrices.
A. Edelman and S. Jeong, "The conditional DPP approach to random matrix distributions." arXiv:2304.09139 (2023).
A. Edelman and S. Jeong, "Fifty three matrix factorizations: A systematic approach." SIAM Journal on Matrix Analysis and Applications (2023).
A. Edelman and S. Jeong, "On the structure of the solutions to the matrix equation G*JG= J." Linear Algebra and its Applications (2022).
A. Edelman and S. Jeong, "On the Cartan decomposition for classical random matrix ensembles." Journal of Mathematical Physics 63.6 (2022): 061705.