Welcome to Tianyun Tang's Homepage

About Me

I am currently a research fellow at Institute of Operations Research and Analytics (IORA) in National University of Singapore. I obtained my Ph.D. degree in 2024 from the Department of Mathematics, National University of Singapore under the supervision of Prof. Kim-Chuan Toh. Back in 2020, I received my B.S. degree from the School of Mathematical Sciences, University of Science and Technology of China.

My CV

Contact Me

• Email: ttydp123@gmail.com
• Email: ttang@u.nus.edu

Research Interests

• Matrix Optimization
• Riemannian optimization
• Scientific computing
• Combinatorics

Pre-prints

Google Scholar

• Optimization over convex polyhedra via Hadamard parametrizations, Tianyun Tang and Kim-Chuan Toh, submitted.
• Exploring chordal sparsity in semidefinite programming with sparse plus low-rank data matrices, Tianyun Tang and Kim-Chuan Toh, submitted.
• Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition, Ching-Pei Lee, Ling Liang, Tianyun Tang and Kim-Chuan Toh, submitted.

Publications

• A feasible method for general convex low-rank SDP problems, Tianyun Tang and Kim-Chuan Toh, SIAM Journal On Optimization, 34.3 (2024): 2169-2200.
• A Riemannian dimension-reduced second order method with application to sensor network localization, Tianyun Tang, Kim-Chuan Toh, Nachuan Xiao and Yinyu Ye, SIAM Journal on Scientific Computing, 46(3), A2025-A2046.
• Self-adaptive ADMM for semi-strongly convex problems, Tianyun Tang and Kim-Chuan Toh, Mathematical Programming Computation, 16(1), 113-150.
• Solving graph equipartition SDPs on an algebraic variety, Tianyun Tang and Kim-Chuan Toh, Mathematical Programming, 204(1), 299-347.
• A feasible method for solving an SDP relaxation of the quadratic knapsack problem, Tianyun Tang and Kim-Chuan Toh, Mathematics of Operations Research, 49(1), 19-39.
• Minimizing cycles in tournaments and normalized q-norms, Jie Ma and Tianyun Tang, Combinatorial Theory 2(3) (2022), #6.
• Monochromatic subgraphs in iterated triangulations, Jie Ma, Tianyun Tang and Xingxing Yu, Electronic Journal of Combinatorics 27(4) (2020), P4.18.

Talks and presentations

• A feasible method for general convex low-rank SDP problems, the 25th International Symposium on Mathematical Programming, Montreal, Canada
• A feasible method for general convex low-rank SDP problems, 2024 INFORMS Optimization Society Conference, Rice University, Houston, Texas, U.S.
• A feasible method for solving an SDP relaxation of the quadratic knapsack problem, 2023 INFORMS Annual Meeting, Phoenix, Arizona, U.S.
• Solving graph equipartition SDPs on an algebraic variety, The 10th International Congress on Industrial and Applied Mathematics, Waseda University, Tokyo, Japan.
• Solving graph equipartition SDPs on an algebraic variety, 2023 SIAM Conference on Optimization, The Sheraton Grand Seattle, Seattle, Washington, U.S.