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Chuan He

Assistant Professor

I am an Assistant Professor in the Division of Applied Mathematics (TIMA) and am also affiliated with WASP at Linköping University. I work on continuous optimization, machine learning, and their intersection.

Synergizing Optimization and Data Science

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.

Before joining LiU, I was a postdoctoral associate and obtained my PhD at the University of Minnesota. I completed my undergraduate studies at Xiamen University.

CV in brief

Employment

  • Assistant Professor in Optimization, Linköping University, Linköping, Sweden
    September 2024 - Present
  • Postdoctoral Associate in Computer Science and Engineering, University of Minnesota, Minneapolis, USA
    Supervisor: Professor Ju Sun
    Oct 2023 – July 2024
    ​

Education

  • Ph.D. in Industrial and Systems Engineering, University of Minnesota Minneapolis, USA
    Advisor: Professor Zhaosong Lu
    Sep 2019 – Sep 2023
  • B.S. in School of Mathematical Sciences, Xiamen University Xiamen, China
    Supervisor: Professor Wen Huang
    Sep 2015 – July 2019

Conference activities

Presentations

  1. “Newton-CG Methods under H¨older Conditions”
    - INFORMS Annual Meeting, Seattle, USA, Oct 2024.
  2. “Augmented Lagrangian Methods for Constrained Optimization in Machine Learning”
    - INFORMS Annual Meeting, Phoenix, USA, Oct 2023.
  3. “Second-Order Learning via Newton-CG Based Methods”
    - Applied Math conference, Shenzhen University, Shenzhen, China, July 2023.
    - SIAM Conference on Optimization, Seattle, USA, June 2023.
    - Applied Math Seminar, Southern University of Science and Technology, Shenzhen, China, May 2021.
  4. “Decision Rule Approaches for Bilevel Linear Programs”
    - INFORMS Annual Meeting, Virtual presentation, Nov 2020.

Conference activities

Posters

  1. “Federated Learning with Convex Constraints”
    - NeurIPS OPT Workshop, New Orleans, USA, Dec 2023.
  2. “Novel Algorithms for Nonconvex Second-Order Optimization with Performance Guarantees”
    - Workshop on Continuous Optimization, Foundation of Computational Mathematics (FoCM) Conference, Paris, France, June 2023.
    ​

More information about me: 

https://chuanhe97.github.io/

 

Research

abstract image with algorithms and digital symbols

WASP at Department of Mathematics (MAI)

This page is about WASP Mathematics. You can read about our two research groups: Mathematics and algorithms for intelligent decision-making, Optimisation for machine learning.

Publications

2024

Chuan He, Heng Huang, Zhaosong Lu (2024) A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization Computational optimization and applications (Article in journal) Continue to DOI
  • Chuan He, Le Peng, Ju Sun, “Federated learning with convex global and local constraints”, Transactions on Machine Learning Research, 2024.
  • Akshit Goyal, Yiling Zhang, Chuan He, “Decision rule approaches for pessimistic bilevel linear programs under moment ambiguity with facility location applications”, INFORMS Journal on Computing, 35(6):1342-1360, 2023.
  • Masaru Ito, Zhaosong Lu, Chuan He, “A parameter-free conditional gradient method for composite minimization under H¨older condition”, Journal of Machine Learning Research, 24(166):1-34, 2023.
  • Chuan He, Zhaosong Lu, “A Newton-CG based barrier method for finding a second-order stationary point of nonconvex conic optimization with complexity guarantees”, SIAM Journal on Optimization, 33(2):1191–1222, 2023.
  • Chuan He, Zhaosong Lu, Ting Kei Pong, “A Newton-CG based augmented Lagrangian method for finding a second-order stationary point of nonconvex equality constrained optimization with complexity guarantees”, SIAM Journal on Optimization, 33(3):1734-1766, 2023.

Organisation

Illustrative picture representing mathematics

Applied Mathematics (TIMA)

Applied mathematics is used to study advanced methods for modeling in technology as well as natural and social sciences. The division conducts research in computational mathematics, mathematical statistics and optimization.
Fractal Plant

Department of Mathematics (MAI)

The department conducts research in computational mathematics, mathematics and applied mathematics, mathematical statistics, and optimization. We provide courses to students in most degree programmes in mathematics, science and engineering.
Studenthuset on Campus Valla in Linköping

About LiU

Linköping University, LiU, offers innovative education and boundary-crossing research. The students are among the most desirable in the labour market and international rankings consistently place LiU as a leading global university.

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