Publications

Prof. Jinghui Zhong has published more than 150 papers, including more than 40 IEEE/ACM Transactions articles. His work has received over 5,800 citations (h-index 37). This page lists representative work by research direction. The complete list is on Google Scholar.

Book

• Jinghui Zhong. 遗传编程算法及其应用 (Genetic Programming Algorithms and Their Applications, in Chinese). Science Press, 2026. Companion code and resources.

Recent Preprints (2026)

• Ziyang Fang, JinXi Wang, Jinghui Zhong, Yew-Soon Ong. TriVAL: A Tri-Validation Framework for Faithful Automatic Optimization Modeling. arXiv:2605.23966, 2026. TriVAL checks the semantic specification, the mathematical formulation, and the solver code in a construct-validate-revise loop. We also introduce NL4COP, a benchmark of 50 combinatorial problem types and 150 instances.
• Min-Yi Zheng, Shengqi Zhang, Liancheng Wu, Jinghui Zhong, Shiyi Chen, Yew-Soon Ong. LawMind: A Law-Driven Paradigm for Discovering Analytical Solutions to Partial Differential Equations. arXiv:2603.14353, 2026. LawMind builds closed-form PDE solutions from governing laws alone, without data. It recovers the solutions of all 100 benchmark PDEs.

Symbolic Regression & Genetic Programming

• Junlan Dong, Jinghui Zhong. Recent Advances in Symbolic Regression. ACM Computing Surveys, 57(11): 1–37, 2025.
• Min-Yi Zheng, Yueheng Wang, Jinghui Zhong, Jun Zhang. Discovering Infinite Recursive Conjectures Through Genetic Programming. IEEE Transactions on Evolutionary Computation, 30(3): 1240–1254, 2026.
• Jinghui Zhong, Junlan Dong, Wei-Li Liu, Liang Feng, Jun Zhang. Multiform Genetic Programming Framework for Symbolic Regression Problems. IEEE Transactions on Evolutionary Computation, 29(2): 429–443, 2025.
• Zhitong Ma, Jinghui Zhong. GESR: A Geometric Evolution Model for Symbolic Regression. Evolutionary Computation, 2026.
• Junlan Dong, Jinghui Zhong, Wei-Li Liu, Jun Zhang. Evolving Equation Learner for Symbolic Regression. IEEE Transactions on Evolutionary Computation, 29(5): 1745–1759, 2025.
• Xiaoxu Han, Jinghui Zhong, Zhitong Ma, Xin Mu, Nikola Gligorovski. Transformer-Assisted Genetic Programming for Symbolic Regression. IEEE Computational Intelligence Magazine, 20(2): 58–79, 2025.
• Zhixing Huang, Yi Mei, Jinghui Zhong. Semantic Linear Genetic Programming for Symbolic Regression. IEEE Transactions on Cybernetics, 54(2): 1321–1334, 2024.
• Jinghui Zhong, Liang Feng, Wentong Cai, Yew-Soon Ong. Multifactorial Genetic Programming for Symbolic Regression Problems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(11): 4492–4505, 2020.
• Jinghui Zhong, Liang Feng, Yew-Soon Ong. Gene Expression Programming: A Survey. IEEE Computational Intelligence Magazine, 12(3): 54–72, 2017.
• Jinghui Zhong, Yew-Soon Ong, Wentong Cai. Self-Learning Gene Expression Programming. IEEE Transactions on Evolutionary Computation, 20(1): 65–80, 2016. Code

Evolutionary Multitasking & Intelligent Optimization

• Tingyang Wei, Shibin Wang, Jinghui Zhong, Dong Liu, Jun Zhang. A Review on Evolutionary Multitask Optimization: Trends and Challenges. IEEE Transactions on Evolutionary Computation, 26(5): 941–960, 2022.
• Shijia Huang, Jinghui Zhong, Wei-Jie Yu. Surrogate-Assisted Evolutionary Framework with Adaptive Knowledge Transfer for Multi-Task Optimization. IEEE Transactions on Emerging Topics in Computing, 9(4): 1930–1944, 2021.
• Liang Feng, Lei Zhou, Jinghui Zhong, Abhishek Gupta, Yew-Soon Ong, Kay-Chen Tan, A. K. Qin. Evolutionary Multitasking via Explicit Autoencoding. IEEE Transactions on Cybernetics, 49(9): 3457–3470, 2019.
• Yongliang Chen, Jinghui Zhong, Liang Feng, Jun Zhang. An Adaptive Archive-Based Evolutionary Framework for Many-Task Optimization. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(3): 369–384, 2020. IEEE TETCI Outstanding Paper Award, 2023.
• Lei Zhou, Liang Feng, Kay Chen Tan, Jinghui Zhong, Zexuan Zhu, Kai Liu, Chao Chen. Toward Adaptive Knowledge Transfer in Multifactorial Evolutionary Computation. IEEE Transactions on Cybernetics, 51(5): 2563–2576, 2021.
• Liang Feng, Yuxiao Huang, Lei Zhou, Jinghui Zhong, Abhishek Gupta, Ke Tang, Kay Chen Tan. Explicit Evolutionary Multitasking for Combinatorial Optimization: A Case Study on Capacitated Vehicle Routing Problem. IEEE Transactions on Cybernetics, 51(6): 3143–3156, 2021.
• Jinghui Zhong, Meie Shen, Jun Zhang, Henry S.H. Chung, Yu-Hui Shi, Yun Li. A Differential Evolution Algorithm With Dual Populations for Solving Periodic Railway Timetable Scheduling Problem. IEEE Transactions on Evolutionary Computation, 17(4): 512–527, 2013.
• Jun Zhang, Zhi-hui Zhan, Ying Lin, Ni Chen, Yue-jiao Gong, Jing-hui Zhong, Henry S.H. Chung, Yun Li, Yu-hui Shi. Evolutionary Computation Meets Machine Learning: A Survey. IEEE Computational Intelligence Magazine, 6(4): 68–75, 2011.

Deep Reinforcement Learning, Crowd Modeling & Complex Systems

• Xiaoxu Han, Xin Mu, Jinghui Zhong. HGFF: A Deep Reinforcement Learning Framework for Lifetime Maximization in Wireless Sensor Networks. IEEE Transactions on Artificial Intelligence, 6(4): 859–873, 2025.
• Xiao-Cheng Liao, Wei-Neng Chen, Xiao-Qi Guo, Jinghui Zhong, Da-Jiang Wang. DRIFT: A Dynamic Crowd Inflow Control System Using LSTM-Based Deep Reinforcement Learning. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 55(6): 4202–4215, 2025.
• Jinghui Zhong, Dongrui Li, Zhixing Huang, Chengyu Lu, Wentong Cai. Data-Driven Crowd Modeling Techniques: A Survey. ACM Transactions on Modeling and Computer Simulation, 32(1): 1–33, 2022.
• Jinghui Zhong, Zhixing Huang, Liang Feng, Wan Du, Ying Li. A Hyper-Heuristic Framework for Lifetime Maximization in Wireless Sensor Networks With a Mobile Sink. IEEE/CAA Journal of Automatica Sinica, 7(1): 223–236, 2020.
• Jinghui Zhong, Wentong Cai, Linbo Luo, Mingbi Zhao. Learning Behavior Patterns From Video for Agent-Based Crowd Modeling and Simulation. Autonomous Agents and Multi-Agent Systems, 30(5): 990–1019, 2016.

Engineering Applications

• Wei-Li Liu, Jinghui Zhong, Peng Liang, Jianhua Guo, Huimin Zhao, Jun Zhang. Towards Explainable Traffic Signal Control for Urban Networks Through Genetic Programming. Swarm and Evolutionary Computation, 88: 101588, 2024.
• Xiao-Cheng Liao, Wei-Neng Chen, Xiao-Qi Guo, Jinghui Zhong, Xiao-Min Hu. Crowd Management Through Optimal Layout of Fences: An Ant Colony Approach Based on Crowd Simulation. IEEE Transactions on Intelligent Transportation Systems, 24(9): 9137–9149, 2023.
• Yu Bai, Pei-Fa Sun, Tian-Hong Wang, Bing Sun, Wei-Jie Yu, Jing-Hui Zhong, Guo-Huan Song, Sang-Woon Jeon, Sam Tak Wu Kwong, Jun Zhang. UAV Path Planning for Data Collection From Wireless Sensor Network With Matrix-Based Evolutionary Computation. IEEE Transactions on Intelligent Transportation Systems, 26(9): 13672–13687, 2025.

Speech & Language

• Chenglong Jiang, Ying Gao, Wing W.Y. Ng, Jiyong Zhou, Jinghui Zhong, Hongzhong Zhen. SeDepTTS: Enhancing the Naturalness via Semantic Dependency and Local Convolution for Text-to-Speech Synthesis. Proceedings of the AAAI Conference on Artificial Intelligence, 37(11): 12959–12967, 2023.

View the complete list on Google Scholar →