Thanh Phat Vo
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Assistant Professor,
Mathematics
- Nonsmooth Optimization, Variational Analysis
Contact Info
- Email: thanh.vo.1@UND.edu
- Office: 701.777.4827
Office Address
Mathematics
Witmer Hall Room 313
101 Cornell Street Stop 8376
Grand Forks, ND 58202-8376
Biography
Dr. Thanh Phat Vo earned his Ph.D. in Applied Mathematics from Wayne State University. His research focuses on nonsmooth optimization and variational analysis, with a goal of making significant contributions to the field by investigating both its theoretical and practical aspects. His work aims to deepen the understanding of key tools in variational analysis while exploring their applications in areas such as statistics, machine learning, and image processing.
In addition to his research, Dr. Vo has extensive teaching experience across a variety of levels, from high school to graduate courses, both in his home country of Vietnam and in the United States. For more details about his research and teaching, visit his website: https://sites.google.com/view/vtphat204.
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Doctor of Philosophy in Applied Mathematics, Wayne State University, Detroit, Michigan, USA (June 2024)
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Master’s Degree in Applied Mathematics, Wayne State University, Detroit, Michigan, USA (May 2021)
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Bachelor’s Degree in Mathematics Teacher Education, Ho Chi Minh City University of Education, Ho Chi Minh City, Vietnam (June 2018)
His main research areas are nonsmooth optimization and variational analysis. He is interested in both theoretical and numerical aspects with applications in machine learning and statistics. To provide further clarity, his research projects can be categorized into three distinct parts:
Qualitative Research: optimality conditions for nonsmooth optimization problems, properties of generalized convexity and monotonicity, stability, regularity, etc.
Quantitative Research: generalized first- and second-order numerical methods for solving nonsmooth nonconvex optimization problems including unconstrained optimization problems, constrained optimization problems, composite optimization problems, difference programming, bilevel optimization, stochastic optimization, etc.
Applications: applying results in qualitative and quantitative studies for real practical optimization models in other fields such as machine learning, statistics, economics, neural networks, wireless systems, etc.
- (with P. D. Khanh and B. S. Mordukhovich) Coderivative-Based Newton Methods in Structured Nonconvex and Nonsmooth Optimization, to appear in Mathematical Programming, (2026) arxiv
- (with P. D. Khanh, B. S. Mordukhovich and L. D. Viet) Generalized Twice Differentiability and Quadratic Bundles in Second-Order Variational Analysis, to appear in Set-Valued and Variational Analysis, (2026) arxiv
- (with P. D. Khanh, B. S. Mordukhovich and L. D. Viet) Characterizations of Strong Variational Convexity and Tilt Stability via Quadratic Bundles, to appear in Journal of Convex Analysis, (2026) arxiv
- (with P. D. Khanh, V. V. H. Khoa and L. D. Viet) Lipschitz Modulus of Convex Functions via Functions Values, Optimization Letters, 20, 197–212 (2026) arxiv Journal
- (with P. D. Khanh, V. V. H. Khoa and B. S. Mordukhovich) Local Minimizers of Nonconvex Functions in Banach Spaces via Moreau Envelopes, Vietnam Journal of Mathematics, 53, 803–813 (2025) arxiv Journal
- (with P. D. Khanh, V. V. H. Khoa and B. S. Mordukhovich) Local maximal monotonicity in variational analysis and optimization, Mathematics of Operations Research, https://doi.org/10.1287/moor.2023.0270 (2025) arxiv Journal
- (with P. D. Khanh, V. V. H. Khoa and B. S. Mordukhovich) Second-Order Subdifferential Optimality Conditions in Nonsmooth Optimization, SIAM Journal on Optimization, 35(2), 678-711 (2025) arxiv Journal
- (with P. D. Khanh, B. S. Mordukhovich and D. B. Tran) Inexact proximal methods for weakly convex functions, Journal of Global Optimization, 91(3), 611-646 (2025) arxiv, Journal
- (with P. D. Khanh, V. V. H. Khoa and B. S. Mordukhovich) Variational and Strong Variational Convexity in Infinite-Dimensional Variational Analysis, SIAM Journal on Optimization, 34(3), 2756-2787 (2024) arxiv, Journal
- (with P. D. Khanh, B. S. Mordukhovich and D. B. Tran) Globally Convergent Coderivative-Based Generalized Newton Methods in Nonsmooth Optimization. Mathematical Programming, 205(1), 373-429 (2024) arxiv, Journal
- (with P. D. Khanh and B. S. Mordukhovich) Variational Convexity of Functions and Variational Sufficiency in Optimization, SIAM Journal on Optimization, 33(2), 1121-1158 (2023) arxiv, Journal
- (with P. D. Khanh and B. S. Mordukhovich) A generalized Newton method for subgradient systems. Mathematics of Operations Research, 48(4), 1811-1845 (2023) arxiv, Journal
- (with P. D. Khanh, B. S. Mordukhovich and D. B. Tran) Generalized damped Newton algorithms in nonsmooth optimization via second-order subdifferentials. Journal of Global Optimization, 86(1), 93-122 (2023) arxiv, Journal
- (with P. D. Khanh) Second-order characterizations of quasiconvexity and pseudoconvexity for differentiable functions with Lipschitzian derivatives. Optimization Letters, 14(8), 2413-2427 (2020) PDF, Journal
- (with P. D. Khanh) Second-order characterizations of C1-smooth robustly quasiconvex functions. Operations Research Letters, 46(6), 568-572 (2018) PDF, Journal