معرفی
Andrei Draganescu is an Associate Professor in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC). He holds a Ph.D. in Applied Mathematics from the University of Chicago (2004) and a B.Sc. in Mathematics from the University of Bucharest, Romania (1993). Before joining UMBC in 2006, he completed a postdoctoral appointment at Sandia National Laboratories. He currently serves as the Graduate Program Director for the Applied Mathematics program at UMBC.
His research focuses on numerical analysis of partial differential equations, particularly multilevel algorithms for PDE-constrained optimization. He has led or co-led multiple grants funded by the National Science Foundation (NSF) and Department of Energy (DOE), including projects on multigrid methods, optimal control of PDEs, and optimization-based domain decomposition.
Draganescu has advised several Ph.D. students and postdocs, including Sumaya Alzuhairy (2021), Mona Hajghassem (2017), and Jyoti Saraswat (2014). His publications span topics such as multigrid preconditioning, PDE-constrained optimization, and numerical linear algebra, with contributions to journals like SIAM Journal on Numerical Analysis and Numerical Linear Algebra with Applications.
He has organized conferences such as the 2024 Fall Finite Element Circus and the Sayas Numerics Days. His teaching spans graduate and undergraduate courses in numerical analysis, matrix analysis, and differential equations.
