معرفی
David Huckleberry Gutman is an Assistant Professor in the Department of Industrial & Systems Engineering (ISEN) at Texas A&M University. He holds a Ph.D. in Mathematical Sciences from Carnegie Mellon University (2019), an M.S. in Mathematics from Tulane University (2010), and a B.S.B.A. in Finance & Accounting from Georgetown University (2008).
- Education:
- Ph.D. in Mathematical Sciences, Carnegie Mellon University, 2019
- M.S. in Mathematics, Tulane University, 2010
- B.S.B.A. in Finance & Accounting, Georgetown University, 2008
His research focuses on continuous optimization theory, emphasizing large-scale optimization methods and optimization over manifolds. He has developed innovative algorithms such as tangent subspace descent for Riemannian manifolds and advanced proximal gradient methods with convergence guarantees.
Key awards include the 2023 NSF CAREER Award and the 2022 INFORMS Optimization Society Young Researcher Prize (jointly with Nam Ho-Nguyen). His work bridges theoretical optimization with practical machine learning and engineering applications.
Advising: Currently mentoring PhD students Allan Gurwicz, George Lobo, and Leandro Maia. Previously held positions at Texas Tech University (2019-2023) and conducted research at Bosch Research and IBM.
Labs/Teams: Leads an active research group at Texas A&M exploring optimization algorithms for modern computational challenges, though no open PhD spots are available at this time.
