Chuan He
Assistant Professor Department of MathematicsLinköping University 🏡🚘🚴Chuan He
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I am an Assistant Professor in the Department of Mathematics and am also affiliated with WASP at Linköping University.
I am an Assistant Professor in the Department of Mathematics and am also affiliated with WASP at Linköping University.
I was a postdoctoral associate in the Department of Computer Science and Engineering at Universitof Minnesota, working with Professor Ju Sun. I earned my PhD from the Department of Industrial and Systems Engineering at University of Minnesota under the supervision of Professor Zhaosong Lu. I received my bachelor's degree from the School of Mathematical Sciences at Xiamen University, with thesis advised by Professor Wen Huang.
I was a postdoctoral associate in the Department of Computer Science and Engineering at Universitof Minnesota, working with Professor Ju Sun. I earned my PhD from the Department of Industrial and Systems Engineering at University of Minnesota under the supervision of Professor Zhaosong Lu. I received my bachelor's degree from the School of Mathematical Sciences at Xiamen University, with thesis advised by Professor Wen Huang.
My research interests center around data science and optimization, with topics including deep learning, decentralized optimization, large-scale optimization, and high-order methods. I am also interested in applications of machine learning in healthcare, scientific computing, image science, and engineering.
My research interests center around data science and optimization, with topics including deep learning, decentralized optimization, large-scale optimization, and high-order methods. I am also interested in applications of machine learning in healthcare, scientific computing, image science, and engineering.
News 🗞️
News 🗞️
Upcoming
[Jun 2-5, 2026]: I will give a talk on "Exploring low-rank structure in Muon" at SIAM Conference on Optimization (OP26), Edinburgh, United Kingdom.
[Jun 3-4, 2026]: I will give a turtorial at Decentralized Learning Workshop, Linköping, Sweden.
[Aug 20-21, 2026]: I will give a talk at WASP BULs Workshop, Stockholm, Sweden.
Past
[Apr 1, 2026]: Our paper "Adaptive Newton-CG methods with global and local analysis for unconstrained optimization with Hölder continuous Hessian" (with Ziyang Zeng and Junyu Zhang) is available online.
[Mar 20-22, 2026]: I organized a session on "Recent advances in stochastic and large-scale optimization" and gave a talk titled "Stochastic optimization methods under heavy-tailed noise" at INFORMS Optimization Society Conference (IOS 2026), Georgia Tech, United States.
[Mar 2-4, 2026]: I gave a talk on "Convex optimization under heavy-tailed noise" at European Convex Optimization Workshop (ECOW), Bremen, Germany.
[Mar 1, 2026]: Our paper "Bayesian optimisation for the experimental sciences: A practical guide to data-efficient optimisation of laboratory workflows" (with Martin Singull and T. Jesper Jacobsson) is published on Advanced Intelligent Systems.
[Feb 26, 2026]: Our paper "Modeling long-term tree growth curves indirectly with piecewise linear regression and explaining factors, when tree ages are unknown" (with Martin Ricker, Dietrich von Rosen, Genaro Gutiérrez-García, Elena Prieto-Rodao, and Martin Singull) is published on Environmental and Ecological Statistics.
[Dec 17, 2025]: Our paper "Bias-variance trade-off for clipped stochastic first-order methods: From bounded variance to infinite mean" is available online.
[Nov 2, 2025]: Our paper "Stochastic interior-point methods for smooth conic optimization with applications" (with Zhanwang Deng) is accepted by Journal of Machine Learning Research.
[Oct 14, 2025]: Our paper "Accelerated stochastic first-order method for convex optimization under heavy-tailed noise" (with Zhaosong Lu) is available online.
[Oct 1, 2025]: Our paper "DeMuon: A decentralized Muon for matrix optimization over graphs" (with Shuyi Ren, Jingwei Mao and Erik G. Larsson) is available online.
[Sep 15, 2025]: Our paper "Low-rank orthogonalization for large-scale matrix optimization with applications to foundation model training" (with Zhanwang Deng and Zhaosong Lu) is available online.
[Sep 2-5, 2025]: I gave a talk on "Stochastic first-order methods can leverage arbitrarily order smoothness for acceleration" at International Conference on Operations Research 2025 (OR 2025), Bielefeld University, Germany.
[July 17, 2025]: Our paper "Exact reformulation and optimization for direct metric optimization in binary imbalanced classification" (with Le Peng, Yash Travadi, Ying Cui, and Ju Sun) is available online.
[July 17, 2025]: Our paper "Faster stochastic cubic regularized Newton methods with momentum" (with Yiming Yang, Xiao Wang, and Zheng Peng) is available online.
[Jun 29-July 2, 2025]: I organized a session on "Recent advances in stochastic optimization" and gave a talk titled "Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise" at the 22nd EUROPT Conference on Advances in Continuous Optimization (EUROPT 2025), University of Southampton, United Kingdom.
[Jun 16-19, 2025]: I presented a poster on "Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise" at LION 19, Prague, Czech Republic.
[Jun 12, 2025]: Our paper "Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise" (with Zhaosong Lu, Defeng Sun and Zhanwang Deng) is available online.
[Apr 19, 2025]: Our paper "Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian" (with Heng Huang and Zhaosong Lu) is accepted by Mathematics of Operations Research.
[Jan 16, 2025]: I gave a talk on "Optimization for Machine Learning" at the WASP Winter Conference in Norrköping.
[Dec 17, 2024]: Our paper "Stochastic interior-point methods for smooth conic optimization with applications" (with Zhanwang Deng) is available online.
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