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Mathematics
USA
2026

D-Index & Metrics

Computer Science

D-Index
80
Citations
32203
World Ranking
1064
National Ranking
570

Mathematics

D-Index
83
Citations
38767
World Ranking
119
National Ranking
68

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 2019 - INFORMS John von Neumann Theory Prize
  • 2009 - SIAM Fellow For advances in variational inequalities and complementarity problems in optimization.
  • 2003 - Dantzig Prize, by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS)

Overview

Jong-Shi Pang is affiliated with the University of Southern California in the United States. Their research spans several main fields of study, including Mathematics, Computer Science, and Engineering, with notable focus areas in computational theory, statistics, numerical analysis, operations research, and control systems engineering.

Their work advances topics such as optimization and variational analysis, advanced optimization algorithms, optimization and mathematical programming, risk and portfolio optimization, sparse and compressive sensing techniques, statistical methods and inference, and fuzzy systems and optimization.

Frequent coauthors collaborating with Jong-Shi Pang include Ying Cui, Shaoning Han, Junyi Liu, Ziyu He, and Zhengling Qi.

Notable recent publications by Jong-Shi Pang include:

  • MultiComposite Nonconvex Optimization for Training Deep Neural Networks, 2020, SIAM Journal on Optimization
  • A Study of Piecewise Linear-Quadratic Programs, 2020, Journal of Optimization Theory and Applications
  • Exact Penalization of Generalized Nash Equilibrium Problems, 2020, Operations Research
  • Two-Stage Stochastic Programming with Linearly Bi-parameterized Quadratic Recourse, 2020, SIAM Journal on Optimization
  • On Robustness of Individualized Decision Rules, 2022, Journal of the American Statistical Association

Jong-Shi Pang has frequently published in venues such as arXiv (Cornell University), SIAM Journal on Optimization, Mathematical Programming, Mathematics of Operations Research, and Operations Research.

In addition to journal articles, Jong-Shi Pang has authored book publications, including Modern Nonconvex Nondifferentiable Optimization published by the Society for Industrial and Applied Mathematics in 2021.

Throughout their career, Jong-Shi Pang has been recognized with awards such as the INFORMS John von Neumann Theory Prize in 2019, the SIAM Fellow designation in 2009 for advances in variational inequalities and complementarity problems in optimization, and the Dantzig Prize awarded by SIAM and the Mathematical Optimization Society in 2003.

Best Publications

  • Finite-Dimensional Variational Inequalities and Complementarity Problems

    Francisco Facchinei;Jong-Shi Pang

  • The Linear Complementarity Problem

    Richard W. Cottle;Jong-Shi Pang;Richard E. Stone

  • Finite-dimensional variational inequality and nonlinear complementarity problems: a survey of theory, algorithms and applications

    P. T. Harker;J.-S. Pang

  • Mathematical Programs with Equilibrium Constraints

    Zhi-Quan Luo;Jong-Shi Pang;Daniel Ralph

  • Engineering and Economic Applications of Complementarity Problems

    M. C. Ferris;J. S. Pang

  • Strategic gaming analysis for electric power systems: an MPEC approach

    B.F. Hobbs;C.B. Metzler;J.-S. Pang

  • Oligopolistic competition in power networks: a conjectured supply function approach

    C.J. Day;B.F. Hobbs;Jong-Shi Pang

  • Error bounds in mathematical programming

    Jong-Shi Pang

  • Differential variational inequalities

    Jong-Shi Pang;David E. Stewart

  • Newton's method for B -differentiable equations

    J. S. Pang

  • Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games

    Jong-Shi Pang;Masao Fukushima

  • Nonsmooth Equations: Motivation and Algorithms

    Jong-Shi Pang;Liqun Qi

  • A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing

    Mingyi Hong;Meisam Razaviyayn;Zhi-Quan Luo;Jong-Shi Pang

  • Iterative methods for variational and complementarity problems

    J. S. Pang;D. Chan

  • Convex Optimization, Game Theory, and Variational Inequality Theory

    Gesualdo Scutari;Daniel Palomar;Francisco Facchinei;Jong-shi Pang

  • The Generalized Quasi-Variational Inequality Problem

    D. Chan;J. S. Pang

  • On Dynamic Multi‐Rigid‐Body Contact Problems with Coulomb Friction

    Unknown

  • Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems

    Gesualdo Scutari;Francisco Facchinei;Peiran Song;Daniel P. Palomar

  • Formulation and comparison of algorithms for frictional contact problems

    P. W. Christensen;Anders Klarbring;Jong Shi Pang;Niclas Strömberg

  • NE/SQP: A robust algorithm for the nonlinear complementarity problem

    Jong-Shi Pang;Steven A. Gabriel

  • Complementarity formulations and existence of solutions of dynamic multi-rigid-body contact problems with Coulomb friction

    Jong-Shi Pang;Jong-Shi Pang;Jeffrey C. Trinkle;Jeffrey C. Trinkle

  • Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games

    Unknown

Frequent Co-Authors

Francisco Facchinei
Francisco Facchinei Sapienza University of Rome
Gesualdo Scutari
Gesualdo Scutari Purdue University West Lafayette
Zhi-Quan Luo
Zhi-Quan Luo Chinese University of Hong Kong, Shenzhen
John E. Mitchell
John E. Mitchell Rensselaer Polytechnic Institute
Benjamin F. Hobbs
Benjamin F. Hobbs Johns Hopkins University
Meisam Razaviyayn
Meisam Razaviyayn University of Southern California
Daniel P. Palomar
Daniel P. Palomar Hong Kong University of Science and Technology
Mingyi Hong
Mingyi Hong University of Minnesota
Henry X. Liu
Henry X. Liu University of Michigan–Ann Arbor
Masao Fukushima
Masao Fukushima Kyoto University

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