• 2023 -      Beijing Institute of Mathematical Sciences and Applications (BIMSA)      Associate Professor
• 2023 - 2023      University of Waterloo      Visiting 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

• 2017      Shanghai teaching achievement award (First prize)
• 2017      MCM/ICM 2017 INFORMS best paper award
• 2016      Outstanding teaching award at Shanghai Jiao Tong University (First prize)
• 2015      Excellent teacher’s award at ParisTech-SJTU

• [1] 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(2024), 2, 1852-1878
• [2] 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
• [3] Y.S. Niu, An Accelerated DC Programming Approach With Exact Line Search for the Symmetric Eigenvalue Complementarity Problem, arXiv:2301.09098(2024)
• [4] Y.S. Niu, Hybrid Accelerated DC Algorithms for the Asymmetric Eigenvalue Complementarity Problem, arXiv:2305.12076(2024)
• [5] Yu You, and Yi-Shuai Niu, A Refined Inertial DC Algorithm for DC Programming, Optimization and Engineering, 24(2023), 65-91
• [6] Y. You, Y.S. Niu, A Variable Metric and Nesterov Extrapolated Proximal DCA With Backtracking for A Composite DC Program, Journal of Industrial and Management Optimization, 19(2023), 10, 7716-7734
• [7] 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:1906.01509(2023)
• [8] Y.S. Niu, Y. You, M.F. Benammour, Y.J. Wang, Parallel DCCUT Algorithms for Mixed-Binary Linear Programs, arXiv:2103.00717(2023)
• [9] Y.S. Niu, On the Convergence Analysis of DCA, arXiv:2211.10942(2023)
• [10] Y.S. Niu, R. Glowinski, Discrete Dynamical System Approaches for Boolean Polynomial Optimization, Journal of Scientific Computing, 92(2022), 2, 1-39
• [11] Y.S. Niu, H. Zhang, Power-product Matrix: Nonsingularity, Sparsity and Determinant, Linear and Multilinear Algebra(2022), 1-18
• [12] Y.S. Niu, H.J. Ji, Optimisation Théorie et Algorithmes, Shanghai Jiao Tong University Press(2022)
• [13] Yi-Shuai Niu, Wentao Ding, Junpeng Hu, Wenxu Xu, and Stephane Canu, Spatio-Temporal Neural Network for Fitting and Forecasting COVID-19, arXiv:2103.11860 (2021)
• [14] 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(2021), 7, 2407-2432
• [15] 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(2019), 11363
• [16] 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
• [17] 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(2019), 341-351
• [18] Y.S. Niu, J.J. Judice, H.A. Lethi, D.T. Pham, Improved DC Programming Approaches for Solving Quadratic Eigenvalue Complementarity Problem, Applied Mathematics and Computation, 353(2019), 95-113
• [19] 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
• [20] 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(2015), 203-214
• [21] 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
• [22] G. Ribert, L. Vervisch, P. Domingo, Y.S. Niu, Hybrid transported-tabulated strategy to downsize detailed chemistry for numerical simulation of flames, Flow, Turbulence and Combustion, 92(2014), 1-2, 175-200
• [23] Y.S. Niu, L. Vervisch, D.T. Pham, An optimization-based approach to detailed chemistry tabulation: Automated progress variables definition, Combustion and Flame, 160(2013), 4, 776-785
• [24] 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(2013), 4, 812-829
• [25] L. Vervisch, Y.S. Niu, G. Lodier, P. Domingo, Recent developments in turbulent combustion modeling: automated progress variables definition − Ignition combustion regimes after rapid compression, ICHMT DIGITAL LIBRARY ONLINE(2012), 37-47
• [26] 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(2012), 321-330
• [27] D.T. Pham, Y.S. Niu, An Efficient DC Programming Approach for Portfolio Decision With Higher Moments, Computational Optimization and Applications, 50(2010), 3, 525-554
• [28] Y.S. Niu, D.T. Pham, A DC Programming Approach for Mixed-Integer Linear Programs, Communications in Computer and Information Science, 14(2008), 244-253

Recruiting

• Educational Background: Strong foundational knowledge in mathematics and/or computer science
• Research Interests: Keen interest in optimization theory and algorithms, practical applications such as machine learning, finance, data analysis, 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 is required.
• Postdoctoral Candidates' Requirements: Postdoc candidates should be early-career researchers who have recently obtained or are about to obtain a PhD within the past five years.

Additional Opportunities:

• PhD candidates will have the opportunity to participate in joint training programs with prestigious institutions such as Tsinghua University, Renmin University of China, or the University of Chinese Academy of Sciences.
• All students and postdocs with me will have the chance to engage in collaborative industry projects, including IT companies like Xiaomi.