Zhenzhong WANG

Zhenzhong WANG

The Hong Kong Polytechnic University

Zhenzhong WANG (王贞众)

I will receive my Ph.D. degree in the Department of Computing at The Hong Kong Polytechnic University and join Xiamen University as an Assistant Professor this coming Fall.

During my Ph.D. study, I am supervised by Prof. Kay Chen Tan (Chair Professor, IEEE Fellow) and Prof. Wanyu Lin. I obtained my Bachelor’s degree from Northeastern University, China, and my Master’s degree from Xiamen University, China, supervised by Prof. Min Jiang.

My research interests include computational intelligence and AI for Science. My research goal is to develop cutting-edge learning algorithms to solve complex problems in engineering and scientific fields, such as molecule discovery, material design, and multi-physics field simulation.

Selected Publications

  1. Z. Wang, H. Hua, W. Lin, M. Yang, K. C. Tan, Crystalline Material Discovery in the Era of Artificial Intelligence, Arxiv, 2024. Preprint [repository]

  2. Z. Wang, Z. Lin, W. Lin, M. Yang, M. Zeng, K. C. Tan, Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models, Arxiv, 2024. Preprint

  3. Z. Wang, D. Xu, M. Jiang, K. C. Tan, Spatial-Temporal Knowledge Transfer for Dynamic Constrained Multiobjective Optimization, IEEE Transactions on Evolutionary Computation, 2024. JCR Q1, Top [code]

  4. Z. Wang, L. Cao, W. Lin, M. Jiang, K. C. Tan, Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks, Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024. CCF-A

  5. Z. Wang, Q. Zeng, W. Lin, M. Jiang, K. C. Tan, Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data, IEEE Transactions on Neural Networks and Learning Systems, 2024. JCR Q1, Top

  6. L. Cao, Y. Liu, Z. Wang, D. Xu, K. Ye, K. C. Tan, M. Jiang, An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations, Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024. CCF-A

  7. Z. Wang, L. Cao, L. Feng, M. Jiang, K. C. Tan, Evolutionary Multitask Optimization with Lower Confidence Bound-Based Solution Selection Strategy, IEEE Transactions on Evolutionary Computation, 2024. JCR Q1, Top [code]

  8. Z. Wang, Q. Zeng, W. Lin, M. Jiang, K. C. Tan, Robust Graph Meta-Learning via Manifold Calibration with Proxy Subgraphs, Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023. CCF-A [code]

  9. Z. Wang, K. Ye, M. Jiang, J. Yao, N. Xiong, G. Yen, Solving Hybrid Charging Strategy Electric Vehicle based Dynamic Routing Problem via Evolutionary Multi-Objective Optimization, Swarm and Evolutionary Computation, 2022. JCR Q1

  10. Z. Wang, H. Hong, K. Ye, G. Zhang, M. Jiang, K. C. Tan, Manifold Interpolation for Large-Scale Multiobjective Optimization via Generative Adversarial Networks, IEEE Transactions on Neural Networks and Learning Systems, 2021. JCR Q1, Top [code]

  11. M. Jiang, Z. Wang* , L. Qiu, S. Guo, X. Gao* , K. C. Tan, Individual-Based Transfer Learning for Dynamic Multiobjective Optimization, IEEE Transactions on Cybernetics, 2021. JCR Q1, Top

  12. M. Jiang, Z. Wang, H. Hong, G. G. Yen, Knee Point-Based Imbalanced Transfer Learning for Dynamic Multiobjective Optimization, IEEE Transactions on Evolutionary Computation, 2021. JCR Q1, Top [code]

  13. M. Jiang, Z. Wang, L. Qiu, S. Guo, X. Gao, K. C. Tan, A Fast Dynamic Evolutionary Multiobjective Algorithm via Manifold Transfer Learning, IEEE Transactions on Cybernetics, 2021. JCR Q1, Top [code]

Service

Reviewer/PC Member for

  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Cybernetics
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Computational Intelligence Magazine
  • IEEE Transactions on Artificial Intelligence
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • IEEE Transactions on Cognitive and Developmental Systems
  • AAAI Conference on Artificial Intelligence
  • Complex & Intelligent Systems
  • International Joint Conference on Neural Networks