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Summary

Computational researcher in applied mathematics, optimization, and machine learning with experience designing and analyzing optimization algorithms for large-scale machine learning models. My work translates mathematical optimization into high-performance implementations, including modern fine-tuning and model-compression techniques that make models smaller and more accurate.

Education

• Ph.D. in Applied Mathematics, Oakland University, Rochester, Michigan, 2022-present
• M.S. in Applied Statistics, Oakland University, Rochester, Michigan
• Mathematics Teacher Education, University of Education, Ho Chi Minh City, Vietnam, 2017-2021

Relevant Coursework

Machine Learning; Deep Learning; Advanced Convex Optimization; Nonlinear Programming; Applied Linear Models; Experimental Design; Mathematical Statistics; Time Series; Numerical Methods for PDEs; Numerical Matrix Algorithms.

Publications

Inexact DC algorithms in Hilbert spaces with applications to PDE-constrained optimization

P. D. Khanh, V. V. H. Khoa, B. S. Mordukhovich, D. B. Tran, and Nghia Van Vo. "Inexact DC algorithms in Hilbert spaces with applications to PDE-constrained optimization." arXiv:2601.06622, submitted to Applied Mathematics & Optimization, 2026.

Adaptive temperature scaling for knowledge distillation via entropy-regularized supervision

H.-C. Luong, Kaiqi Zhao, L. Chen, and Nghia Van Vo. "Adaptive temperature scaling for knowledge distillation via entropy-regularized supervision." Submitted, 2026.

Nonsmooth Newton methods with effective subspaces for polyhedral regularization

Tran T. A. Nghia, Khoa V. H. Vu, and Nghia Van Vo. "Nonsmooth Newton methods with effective subspaces for polyhedral regularization." arXiv:2511.16514, submitted to Mathematics of Operations Research, 2025.

Stable recovery of regularized linear inverse problems

Tran T. A. Nghia, Huy P. N., and Nghia Van Vo. "Stable recovery of regularized linear inverse problems." Inverse Problems 41, 065018. DOI: 10.1088/1361-6420/addffb, 2025.

A regularity result via fractional maximal operators for p-Laplace equations in weighted Lorentz spaces

C.-K. Doan, G.-B. Nguyen, and Nghia Van Vo. "A regularity result via fractional maximal operators for p-Laplace equations in weighted Lorentz spaces." Complex Variables and Elliptic Equations. DOI: 10.1080/17476933.2021.1897794, 2022.

A gradient estimate related fractional maximal operators for a p-Laplace problem in Morrey spaces

T.-N. Nguyen, M.-P. Tran, C.-K. Doan, and Nghia Van Vo. "A gradient estimate related fractional maximal operators for a p-Laplace problem in Morrey spaces." Taiwanese Journal of Mathematics, advance publication, 1-21. DOI: 10.11650/tjm/210202, 2021.

Projects

Accelerated Image Processing and Optimization

Model Compression using Adaptive Knowledge Distillation

Premier League Ranking Prediction and Disease Symptom Diagnosis

Teaching

MOR 5555 - Nonlinear Optimization

MTH 2554 - Multivariable Calculus

MTH 1441 - Pre-Calculus

MTH 0662 - Intermediate Algebra

MTH 0661 - Elementary Algebra

Honors and Awards

• McKay Outstanding Graduate Research Fellowship, Oakland University, 2026
• Travel Grant to attend Midwest Optimization Meeting, University of North Dakota, 2025
• Travel Grant to attend East Coast Optimization Meeting, George Mason University, 2025
• Travel Grant to attend Midwest Optimization Meeting, University of Michigan, 2023
• Award for Teaching Excellence Internship, Department of Mathematics, Binh Phu High School, 2021
• First Prize, Department of Mathematics Undergraduate Scientific Research Competition, 2020
• First Prize, Undergraduate Scientific Research Competition, H.C.M City University of Education, 2020

Skills

• Programming: Python, Matlab, SAS, C, SQL
• Optimization: gradient descent, stochastic gradient descent, proximal methods, FISTA, Newton methods, ADMM, Douglas-Rachford, Chambolle-Pock primal-dual, coordinate descent
• Frameworks and tools: Scikit-learn, PyTorch, Pandas, NumPy, Matplotlib, Seaborn, CVXPY, Gurobi, CPLEX, MATLAB Optimization Toolbox, Git, GitHub
• Languages: English, Vietnamese

Certificates

• Introduction to Data Analytics in Google Cloud
• Machine Learning Specialization, Stanford University and Coursera
• Scientific Computing and Data Analysis with Python, FreeCodeCamp
• Mathematics for Machine Learning, Imperial College London and Coursera