Zaiwen Wen
Associate Professor In The Department Of Mathematics And The Institute Of Natural Sciences
Shanghai, Shanghai, China
Summary
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Senior🎓
Top SchoolZaiwen Wen is an associate professor in mathematics at Shanghai Jiao Tong University with deep expertise in large-scale computational and convex optimization, PDE-constrained optimization, and multigrid/multilevel methods. He holds a Ph.D. in Operations Research from Columbia and combines rigorous theory with practical software development for large-scale optimization problems. His work spans scientific and engineering applications including image processing and compressive sensing, and he has translated algorithmic advances into usable code for challenging infinite-dimensional problems. A former NSF Math Institutes postdoc at IPAM, UCLA and Rice, he brings international research experience and collaborations. Based in Shanghai, he is also active in optimization for machine learning, blending academic rigor with an eye toward scalable implementations. Notably, his career bridges classical computational mathematics and modern ML-driven optimization, enabling methods that perform well on both PDEs and data-intensive tasks.
8 years of coding experience
Ph.D, Operations Research, Ph.D, Operations Research at Columbia UniversityMS, Computational Mathematics, MS, Computational Mathematics at Chinese Academy of SciencesBS, Applied Mathematics, BS, Applied Mathematics at Shanghai Jiao Tong University
Github Skills (5)
newton-method7
optimization6
machine-learning1
deep-learning1
gradient1
Programming languages (2)
Github contributions (5)
optsuite/ARNT
Dec 2017 - Jun 2019
Adaptive Regularized Newton Method for Riemannian Optimization
Contributions:5 commits, 3 pushes, 1 branch in 1 year 6 months
adaptiveoptimizationmethodriemannian-optimizationnewton-method
optsuite/OptM
Jul 2018 - Apr 2021
Contributions:12 commits, 10 pushes, 1 branch in 2 years 9 months
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