BIMSA > Yishuai Niu
Associate Professor Yishuai Niu

Yishuai Niu

Associate Professor
Affiliation: BIMSA
Research Field: Optimization, High-Performance Computing, Machine Learning
Office: A6-301
Email: niuyishuai@bimsa.cn
Webpage: https://sites.google.com/view/niuys

Biography

Yi-Shuai Niu, an Associate Professor of Mathematics at Beijing Institute of Mathematical Sciences and Applications (BIMSA), specialized in Optimization, Scientific Computing, Machine Learning, and Computer Sciences. Before joining BIMSA in October 2023, he was a research fellow at the Hong Kong Polytechnic University (2021-2022); an associate professor at Shanghai Jiao Tong University (2014-2021), where he led the “Optimization and Interdisciplinary Research Group” and double-appointed at the ParisTech Elite Institute of Technology and the School of Mathematical Sciences. His earlier roles include postdoc at the University of Paris 6 (2013-2014) and junior researcher both at the French National Center for Scientific Research (CNRS) and Stanford University (2010-2012). He was also a lecturer at the National Institute of Applied Sciences (INSA) of Rouen (2007-2010) in France, where he earned a Ph.D. in Mathematics-Optimization in 2010 and double Masters in Pure and Applied Mathematics and Genie Mathematics in 2006. His research covers a wide range of applied mathematics, with a spotlight on optimization theory, machine learning, high-performance computing, and software development. His works span various interdisciplinary applications including: machine learning, natural language processing, self-driving car, finance, image processing, turbulent combustion, polymer science, quantum chemistry and computing, and plasma physics. His contributions encompass fundamental research, emphasizing novel algorithms for large-scale nonconvex and nonsmooth problems, and practical implementations, focusing on efficient optimization solvers and scientific computing packages via HPC. He developed more than 36 pieces of software and published about 40 articles in prestigious journals and conferences (including SIAM Journal on Optimization, Journal of Scientific Computing, Combustion and Flames, Applied Mathematics and Computation). He was PI of 6 research grants (including a Key Project of NSFC) and members of 5 joint international research projects. His honors and distinctions include: Beijing Overseas Talent Programs, core member of the Beijing Strategic Scientist Program, the First Prize of the Shanghai Teaching Achievement Award (2017), the First Prize of the Teaching Achievement Award at Shanghai Jiao Tong University (2016 and 2017), as well as 17 awards in the International Mathematical Contest in Modeling (MCM/ICM), including the INFORMS Best Paper Award in 2017.

Research Interest

  • High-Performance Computing
  • Deep Learning
  • Optimization
  • Turbulent Combustion
  • Laser Induced Breakdown Spectroscopy
  • Image Processing
  • Quantum Computing
  • Natural Language Processing
  • Portfolio Investment
  • Self-driving Car
  • Yau-Yau Filter
  • Yau's Affine Normal Descent

Education Experience

  • 2006 - 2010 | National Institute of Applied Sciences of Rouen, France | Mathematics - Optimization | Doctor | (Supervisor: Pham Dinh Tao)
  • 2005 - 2006 | National Institute of Applied Sciences of Rouen, France | Fundamental and Applied Mathematics | Master
  • 2001 - 2006 | National Institute of Applied Sciences of Rouen, France | Genie Mathematics | Master

Work Experience

  • 2023 - -- | Beijing Institute of Mathematical Sciences and Applications (BIMSA) | Associate Professor
  • 2021 - 2022 | The Hong Kong Polytechnic University | Research Fellow
  • 2018 - 2018 | University of California Irvine | Visiting Professor
  • 2014 - 2021 | Shanghai Jiao Tong University | Associate Professor
  • 2013 - 2014 | University of Paris 6 (UPMC) | Postdoc
  • 2010 - 2012 | French National Center for Scientific Research (CNRS) & Stanford University | Junior Researcher
  • 2007 - 2010 | National Institute of Applied Sciences of Rouen, France | Lecturer

Honors and Awards

  • 2025 | Beijing Overseas High-Level Talent (Innovative Program)
  • 2025 | Beijing High-Level Overseas Scholar
  • 2024 | Ruo Lin Award (Paper Award)
  • 2024 | Core Member of the Beijing Strategic Scientist Program
  • 2017 | MCM/ICM 2017 INFORMS best paper award
  • 2017 | Shanghai teaching achievement award (First prize)
  • 2016 | Outstanding teaching award at Shanghai Jiao Tong University (First prize)
  • 2015 | Excellent teacher’s award at ParisTech-SJTU

Publication

  • [1] Yi-Shuai Niu, Artan Sheshmani, Shing-Tung Yau, Yau's Affine Normal Descent: Algorithmic Framework and Convergence Analysis, arXiv:2603.28448 (2026)
  • [2] Yi-Shuai Niu, Artan Sheshmani, Shing-Tung Yau, Affine Normal Directions via Log-Determinant Geometry: Scalable Computation under Sparse Polynomial Structure, arXiv:2604.01163 (2026)
  • [3] Ya-Juan Wang, Yi-Shuai Niu, Artan Sheshmani, Shing-Tung Yau, Yau's Affine-Normal Descent for Large-Scale Higher-Moment Portfolio Optimization, arXiv:2604.25378 (2026)
  • [4] Yi-Shuai Niu, Yajuan Wang, Scalable Mean-Variance Portfolio Optimization via Subspace Embeddings and GPU-Friendly Nesterov-Accelerated Projected Gradient, arXiv:2604.02917 (2026)
  • [5] Shing-Tung Yau, Yi-Shuai Niu, An Improved Yau-Yau Algorithm for High Dimensional Nonlinear Filtering Problems, Pure and Applied Mathematics Quarterly, 21(6), 2369-2423 (2026)
  • [6] Yi-Shuai Niu, Shing-Tung Yau, Polylab: A MATLAB Toolbox for Multivariate Polynomial Modeling, arXiv:2604.06575 (2026)
  • [7] Yi-Shuai Niu, Continuous-Time Dynamics of the Difference-of-Convex Algorithm, arXiv:2604.06926 (2026)
  • [8] Yi-Shuai Niu, Hoai An Le Thi, and Dinh Tao Pham, On difference-of-sos and difference-of-convex-sos decompositions for polynomials, SIAM Journal on Optimization, 34(2), 1852-1878 (2024)
  • [9] Youran Sun, Yihua Liu, Yi-Shuai Niu, Understand the Effectiveness of Shortcuts through the Lens of DCA, Data Analytics and Topology, 1(2), 109-116 (2025)
  • [10] Yi-Shuai Niu, Yu You, Benammour M. Faouzi, Yajuan Wang, A parallel difference-of-convex cutting plane algorithm for mixed-binary linear programs, Optimization, 1-38 (2025)
  • [11] Y.S. Niu, H.A. Le Thi, D.T. Pham, BDCA with Exact Line Search for Symmetric Eigenvalue Complementarity Problems, Lecture Notes in Networks and Systems, 159-171 (2025)
  • [12] Y.S. Niu, H. Zhang, Power-product matrix: nonsingularity, sparsity and determinant, Linear and Multilinear Algebra, 72(7), 1170-1187 (2024)
  • [13] H. Zhang, Y.S. Niu, A Boosted-DCA with Power-Sum-DC Decomposition for Linearly Constrained Polynomial Program, Journal of Optimization Theory and Applications, 201(2024), 720-759
  • [14] Y.S. Niu, Hybrid Accelerated DC Algorithms for the Asymmetric Eigenvalue Complementarity Problem, arXiv:2305.12076(2024)
  • [15] Yu You and Yi-Shuai Niu, A variable metric and nesterov extrapolated proximal DCA with backtracking for a composite DC program, Journal of Industrial and Management Optimization, 19(10), 7716-7734 (2023)
  • [16] YS Niu, Accelerated DC Algorithms for the Asymmetric Eigenvalue Complementarity Problem, arXiv preprint arXiv:2305.12076 (2023)
  • [17] Yu You, and Yi-Shuai Niu, A refined inertial DC algorithm for DC programming, Optimization and Engineering, 24(1), 65-91 (2023)
  • [18] Y.S. Niu, An Accelerated DC Programming Approach with Exact Line Search for The Symmetric Eigenvalue Complementarity Problem, arXiv preprint arXiv:2301.09098 (2023)
  • [19] Y.S. Niu, On the convergence analysis of DCA, arXiv preprint arXiv:2211.10942 (2022)
  • [20] Y.S. Niu, R. Glowinski, Discrete Dynamical System Approaches for Boolean Polynomial Optimization, Journal of Scientific Computing, 92(2), 1-39 (2022)
  • [21] Y.S. Niu, H.J. Ji, Optimisation Théorie et Algorithmes, Shanghai Jiao Tong University Press(2022)
  • [22] Yi-Shuai Niu, Yu You, Wenxu Xu, Wentao Ding, Junpeng Hu, and Songquan Yao, A difference-of-convex programming approach with parallel branch-and-bound for sentence compression via a hybrid extractive model, Optimization Letters, 15, 1-26 (2021)
  • [23] Yi-Shuai Niu, Wentao Ding, Junpeng Hu, Wenxu Xu, and Stephane Canu, Spatio-Temporal Neural Network for Fitting and Forecasting COVID-19, arXiv preprint arXiv:2103.11860 (2021)
  • [24] YS Niu, Y You, A Difference-of-Convex Cutting Plane Algorithm for Mixed-Binary Linear Program, arXiv preprint arXiv:2103.00717 (2021)
  • [25] Y.S. Niu, X.W. Hu, Y. You, F. Benammour, H. Zhang, Sentence compression via dc programming approach, Advances in Intelligent Systems and Computing, 991, 341-351 (2020)
  • [26] Chen Sun, Ye Tian, Liang Gao, Yi-Shuai Niu, Tianlong Zhang, Hua Li, Yuqing Zhang, Zengqi Yue, Nicole Delepine-Gilon, and Jin Yu, Machine Learning Allows Calibration Models to Predict Trace Element Concentration in Soil with Generalized LIBS Spectra, Scientific Reports, 9(1), 11363 (2019)
  • [27] YS Niu, J Júdice, HA Le Thi, DT Pham, Improved dc programming approaches for solving the quadratic eigenvalue complementarity problem, Applied Mathematics and Computation, 353, 95-113 (2019)
  • [28] Y.S. Niu, Y. You, W.Z. Liu, Parallel DC Cutting Plane Algorithms for Mixed Binary Linear Program, Advances in Intelligent Systems and Computing, 991(2019), 330-340
  • [29] Y.S. Niu, Y.J. Wang, H.A. Le Thi, D.T. Pham, High-order moment portfolio optimization via an accelerated difference-of-convex programming approach and sums-of-squares, arXiv preprint arXiv:1906.01509 (2019)
  • [30] D.T. Pham, H.A. Le Thi, V.N. Pham, Y.S. Niu, DC Programming Approaches for Discrete Portfolio Optimization Under Concave Transaction Costs, Optimization Letters, 10(2016), 2, 261-282
  • [31] Y.S. Niu, J.J. Judice, H.A. Lethi, D.T. Pham, Solving the quadratic eigenvalue complementarity problem by DC programming, Advances in Intelligent Systems and Computing, 359, 203-214 (2015)
  • [32] G Ribert, L Vervisch, P Domingo, YS Niu, Hybrid transported-tabulated strategy to downsize detailed chemistry for numerical simulation of premixed flames, Flow, turbulence and combustion, 92(1-2), 175-200 (2014)
  • [33] Y.S. Niu, D.T. Pham, DC Programming Approaches for BMI and QMI Feasibility Problems, Advances in Intelligent Systems and Computing, 282(2014), 37-63
  • [34] Y.S. Niu, D.T. Pham, H.A. Le Thi and J.J. Judice, Efficient DC programming approaches for the asymmetric eigenvalue complementarity problem, Optimization Methods and Software, 28(4), 812-829 (2013)
  • [35] YS Niu, L Vervisch, DT Pham, An optimization-based approach to detailed chemistry tabulation: Automated progress variable definition, Combustion and Flame, 160(4), 776-785 (2013)
  • [36] B.M. Ndiaye, H.A. Le Thi, D.T. Pham, Y.S. Niu, DC programming and DCA for large-scale two-dimensional packing problems, Lecture Notes in Computer Science, 7197, 321-330 (2012)
  • [37] L Vervisch, YS Niu, G Lodier, P Domingo, Recent developments in turbulent combustion modeling: automated progress variables definition− Ignition combustion regimes after rapid compression, Proceedings of the Seventh International Symposium On Turbulence (2012)
  • [38] D.T. Pham, Y.S. Niu, An efficient DC programming approach for portfolio decision with higher moments, Computational Optimization and Applications, 50(3), 525-554 (2011)
  • [39] YS Niu, DT Pham, Efficient DC programming approaches for mixed-integer quadratic convex programs, Proceedings of the International Conference on Industrial Engineering and Systems Management (IESM2011), 222-231 (2011)
  • [40] YS Niu, Programmation DC & DCA en Optimisation Combinatoire et Optimisation Polynomiale via les Techniques de SDP, INSA de Rouen (2010)
  • [41] Y.S. Niu, D.T. Pham, A DC programming approach for mixed-integer linear programs, Communications in Computer and Information Science, 14, 244-253 (2008)

Academic Service

  • 2025 - -- | Operations Research Forum | Associate Editor

Other

Recruiting

Seeking assistant professor and highly self-motivated postdocs in optimization. For more details about the positions and how to apply, please feel free to email me directly and see https://www.mathjobs.org/jobs/list/21900 (for postdoc) and https://www.mathjobs.org/jobs/list/27475 (for assistant professor)

Ideal Candidate Profile:
  • Educational Background: Strong foundational knowledge in mathematics and/or computer science
  • Research Interests: Keen interest in optimization theory and algorithms, machine learning and/or dynamical system/nonlinear filtering, differential or algebraic geometry; practical applications such as machine learning, finance, data analysis, biological data processing, weather forecast and data assimilation, image processing, quantum information, and high-performance computing.
  • Language Skills: Must demonstrate fluency in both spoken and written English.
  • Technical Skills: Proficiency in Matlab/Python programming and familiar with High-Performance Computing.
  • Additional Requirements: 
    • For assistant professor positions, preference will be given to candidates with interdisciplinary strengths in optimization + (Differential or Algebraic) geometry + high-performance computing, or optimization + AI.
    • Postdoc candidates should be early-career researchers who have recently obtained or are about to obtain a PhD within the past five years, the age of the candidate must not beyond 35 for Chinese candidates. 
Update Time: 2026-06-21 18:00:07