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Defeng Sun | |
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Nationality | Chinese |
Alma mater | Nanjing University Chinese Academy of Sciences |
Awards | Beale--Orchard-Hays Prize for Excellence in Computational Mathematical Programming 2018 by the Mathematical Optimization Society [1]
Fellow of the Society of Industrial and Applied Mathematics [2] (2020) Inaugural Fellow of China Society of Industrial and Applied Mathematics [3](2020) RGC Senior Research Fellow Award 2022/23 [4] |
Scientific career | |
Fields | Optimization and Machine Learning |
Institutions | Department of Applied Mathematics, The Hong Kong Polytechnic University |
Doctoral advisor | Jiye Han (Chinese name: 韩继业) |
Defeng Sun (Chinese name: 孙德锋) is a Chinese applied mathematician and operations researcher. He holds the position of Chair Professor of Applied Optimization and Operations Research, and has been serving as the Head[6] of Department of Applied Mathematics in The Hong Kong Polytechnic University (PolyU) since 2019. Additional, he is the Director of the Research Centre for Intelligent Operations Research [7](2024 - present) at PolyU, a role he has held since 2024. Beyond his duties at PolyU, Sun had been the President of The Hong Kong Mathematical Society [8](2020) in 2020-2024.
Education
[edit]Sun received his Ph.D. degree in 1995 from Chinese Academy of Sciences in Beijing under the supervision of Professor Jiye Han[9] (Chinese name: 韩继业), after obtaining his bachelor’s and Master’s degree from Nanjing University in 1989 and 1992, respectively.
Research
[edit]Sun’s research interests lie in the broad areas of non-convex continuous optimization and machine learning including mathematical theory, algorithmic developments and real-world applications[10].
Sun is recognized for his 2006 work characterizing the strong regularity of nonlinear semidefinite programming[11] and his software SDPNAL/SDPNAL+ for general purpose large scale semidefinite programming[12]. By employing a majorized semismooth NewtonCG augmented Lagrangian method coupled with a convergent 3-block alternating direction method of multipliers, the software SDPNAL+ has successfully tackled the numerical difficulty its original version faced. Numerical results for various large scale SDPs with or without nonnegative constraints show that the proposed method is not only fast but also robust in obtaining accurate solutions. The work on SDPNAL+ was awarded with the 2018 Beale--Orchard-Hays Prize for Excellence in Computational Mathematical Programming[1].
Awards
[edit]Sun was ranked among the World’s Top 2% most-cited scientists by Stanford University from 2021 to 2024 [13] [14] [15] [16]
He was elected the Fellow of the Society of Industrial and Applied Mathematics, and Inaugural Fellow of China Society of Industrial and Applied Mathematics in 2020 for his contributions to algorithms and software for conic optimization, particularly matrix optimization [2] [3].
He received the RGC Senior Research Fellowship for his project "Nonlinear Conic Programming: Theory, Algorithms and Software" by Hong Kong's University Grants Committee in 2022/23 [4] [17].
References
[edit]- ^ a b "The Beale — Orchard-Hays Prize, Mathematical Optimization Society".
- ^ a b "Society of Industrial and Applied Mathematics Fellow".
- ^ a b "China Society of Industrial and Applied Mathematics Fellow".
- ^ a b "RGC Senior Research Fellow 2022/23".
- ^ "中国运筹学会第十七届年会新闻稿".
- ^ "Sun Defeng, Department of Applied Mathematics, The Hong Kong Polytechnic University. Retrieved October 23, 2024".
- ^ "Structure and members, Research Centre for Intelligent Operations Research".
- ^ "Council Memeber, The Hong Kong Mathematical Society".
- ^ "Mathematics Genealogy Project".
- ^ "Sun's Research Interests".
- ^ "Defeng Sun, "The strong second order sufficient condition and constraint nondegeneracy in nonlinear semidefinite programming and their implications", Final PDF version NLSDP_Final.pdf Mathematics of Operations Research 31 (2006) 761--776" (PDF).
- ^ "Liuqin Yang, Defeng Sun, and Kim Chuan Toh, "SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints", Mathematical Programming Computation Vol. 7, Issue 3 (2015) 331–366" (PDF).
- ^ "Top 2% Most-Cited Scientists by Stanford University, 2021".
- ^ "Top 2% Most-Cited Scientists by Stanford University, 2022".
- ^ "Top 2% Most-Cited Scientists by Stanford University, 2023".
- ^ "Top 2% Most-Cited Scientists by Stanford University, 2024".
- ^ "RGC Award Presentation Ceremony (2022/23)".