Renfeng Peng
Renfeng Peng is a Ph.D. student of the Optimization Group at Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences (CAS), under the supervision of Prof. Ya-xiang Yuan. He received the Bachelor degree (2021) in mathematics and applied mathematics at School of Mathematical Sciences, Tongji University. His research interests include low-rank matrix and tensor optimization, manifold optimization, quantum information science, and machine learning.
Updates
- 2024-05-02: new paper accepted in SIAM Journal on Matrix Analysis and Applications - “Optimization on product manifolds under a preconditioned metric.”
- 2025-04-12: new conference paper accepted in ISIT 2025- “Riemannian optimization for Holevo capacity.”
- 2025-03-07: new preprint - “First-order methods on bounded-rank tensors converging to stationary points.”
- 2025-01-22: new preprint - “Riemannian optimization for Holevo capacity.”
- 2024-12-13: new paper accepted in Mathematical Programming - “Low-rank optimization on Tucker tensor varieties.”
- 2024-11-22: new preprint - “Desingularization of bounded-rank tensor sets.”
- 2024-01-18: new paper accepted in Computational Optimization and Applications - “Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition.”
Looking for a Postdoctoral Position (from July 2026)
I am currently seeking a postdoctoral position starting in July 2026. Please feel free to contact me if you think there might be a good fit.
Education
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University of Chinese Academy of Sciences (2021.09--present)
Academy of Mathematics and Systems Science
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Tongji University (2017.09--2021.07)
School of Mathematical Sciences
Refereed papers & preprints
- A second order numerical scheme for fractional option pricing modelsEast Asian J. Appl. Math, 2021
LRTCTR
A Matlab solver for low-rank tensor completion in tensor ring decomposition.
popman
A Matlab solver for preconditioned Riemannian optimization methods on product manifolds.
TRAM
Tucker rank-adaptive method for Tucker tensor completion.
TuckerDesing
A Matlab solver for low-rank Tucker tensor optimization via desingularization.
TuckerApoFree
First-order methods for low-rank Tucker tensor optimization converging to stationary points.Selected presentations
| Date | Place | Conference |
|---|---|---|
|
2025/07
|
Los Angeles, U.S.
|
International conference on continuous optimization |
|
2024/11
|
Beijing, China
|
The 7th PKU PhD Symposium for Applied Mathematics |