江敏Min Jiang
“人生只有一种英雄主义，那就是认清生活的真相后，仍然热爱生活。”
“There is only one heroism in the world: to see the world as it is, and to love it.”
—— 罗曼·罗兰Romain Rolland
简介About
江敏，厦门大学信息学院人工智能系教授，所在团队为自然计算与仿真实验室。研究方向为演化计算、学习驱动的优化和科学智能，关注智能系统如何在复杂环境中适应、推理并支持决策。
现任 IEEE Computational Intelligence Magazine 主编（2026– ）、IEEE Transactions on Evolutionary Computation 编委，担任 NeurIPS 2026、IJCAI 2024 领域主席。2018 年发表于 IEEE TEVC 的论文将迁移学习引入动态多目标优化；与合作者撰写的演化迁移优化综述获 2024 年 IEEE CIM 杰出论文奖。2023–2026 年入选斯坦福大学与爱思唯尔发布的全球前 2% 顶尖科学家榜单。
2001 年和 2007 年于武汉大学计算机科学专业获学士和博士学位，2005–2007 年在香港城市大学计算机科学系访问。IEEE 高级会员。
研究方向Research
- 学习驱动的演化优化将迁移学习、预训练和大语言模型引入演化搜索，求解动态、大规模和双层优化问题。
- 神经符号知识发现与多物理场仿真符号回归、物理嵌入网络和神经算子，用于耦合系统的建模与仿真。
- AI for Science偏微分方程的可解释求解、可微建模，以及从观测数据中学习物理规律。
近期动态News
- 2026.08担任客座编辑的 IEEE TEVC 特刊 Evolutionary Computation Meets Large Language Models 出版（Vol. 30, No. 4）。
- 20261 篇论文被 NeurIPS 2026 录用；担任 NeurIPS 2026 领域主席。
- 20261 篇论文被 ICLR 2026 录用，4 篇被 AAAI 2026 录用，其中 1 篇为口头报告。
- 2026.01出任 IEEE Computational Intelligence Magazine 主编。
代表性论文Selected Publications
精选
- Transfer Learning-Based Dynamic Multiobjective Optimization AlgorithmsM. Jiang*, Z. Huang, L. Qiu, W. Huang, G. G. Yen · IEEE TEVC 2018提出基于迁移学习的动态多目标优化框架。
- Evolutionary Transfer Optimization — A New Frontier in Evolutionary Computation ResearchK. C. Tan, L. Feng, M. Jiang · IEEE Computational Intelligence Magazine 20212024 IEEE CIM 杰出论文奖。系统阐述演化迁移优化这一新方向。
- Transferable Multiform Attack for Cross-Modal Person Re-IdentificationY. Gong†, C. Yang, Q. Zeng, D. Xu, Z. Luo, Z. Wang, M. Jiang* · NeurIPS 2026
- VisionLaw: Inferring Interpretable Intrinsic Dynamics from Visual Observations via Bilevel OptimizationJ. Lin†, S. Jiang, Q. Zeng, Z. Wang, M. Jiang* · ICLR 2026通过双层优化，从视频中推断可解释的物理规律。
- PEGNet: A Physics-Embedded Graph Network for Long-Term Stable Multiphysics SimulationC. Yang†, Z. Wang, J. Liu, Y. Gong, M. Jiang* · AAAI 2026将物理约束嵌入图网络，实现长时稳定的多物理场仿真。
全部顶会顶刊论文
发表于 CCF-A 会议及领域顶级期刊的论文。† 课题组学生第一作者 * 通讯作者 全部 178 篇论文 →
2026
- Transferable Multiform Attack for Cross-Modal Person Re-IdentificationY. Gong†, C. Yang, Q. Zeng, D. Xu, Z. Luo, Z. Wang, M. Jiang* · NeurIPS 2026
- VisionLaw: Inferring Interpretable Intrinsic Dynamics from Visual Observations via Bilevel OptimizationJ. Lin†, S. Jiang, Q. Zeng, Z. Wang, M. Jiang* · ICLR 2026
- A Theory-Inspired Framework for Few-Shot Cross-Modal Sketch Person Re-IdentificationY. Gong†, Y. Hou, J. Shi, K. L. Diep, M. Jiang* · AAAI 2026, oral
- PEGNet: A Physics-Embedded Graph Network for Long-Term Stable Multiphysics SimulationC. Yang†, Z. Wang, J. Liu, Y. Gong, M. Jiang* · AAAI 2026
- Cross-Field Interface-Aware Neural Operators for Multiphase Flow SimulationZ. Wang†, X. Zhang, J. Liao, M. Jiang* · AAAI 2026
- Fading the Digital Ink: A Universal Black-Box Attack Framework for 3DGS Watermarking SystemsQ. Zeng†, S. Jiang, J. Lin, Z. Wang, K. C. Tan, M. Jiang* · AAAI 2026
- Symbolic Regression with Physics-Informed Residual and Structural Sensitivity PruningY. Gong†, C. Liu, S. Lan, J. Liao, C. Yang, J. Lin, M. Jiang*, G. G. Yen · IEEE TEVC
- Enhancing Generalization and Scalability for Multiobjective Optimization with Population Pre-trainingH. Hong†, L. Feng, M. Jiang, K. C. Tan · Evolutionary Computation
2025
- Phys4DGen: Physics-Compliant 4D Generation with Multi-Material Composition PerceptionJ. Lin†, Z. Wang, D. Xu, S. Jiang, Y. Gong, M. Jiang* · ACM MM 2025
- Interpretable Solutions for Multi-Physics PDEs Using T-NNGPL. Cao†, Z. Lin, K. C. Tan, M. Jiang* · AAAI 2025
- Multispace Dimensionality Reduction Based on Extreme Learning Machine-Assisted Autoencoder for High-Dimensional Expensive OptimizationZ. Wu, W. Song, H. Yu, Y. Guo, M. Jiang, S. Yang · IEEE TEVC
- Gradient-Guided Joint Representation Loss with Adaptive Neck for Train Crash DetectionY. Wen, P. Xu, M. Jiang, W. Xu, C. Yang · IEEE TITS
- Cross-Modality Average Precision Optimization for Visible Thermal Person Re-IdentificationY. Ling, Z. Luo, D. Lin, S. Li, M. Jiang, N. Sebe, Z. Zhong · Pattern Recognition
2024
- Cross-Modality Perturbation Synergy Attack for Person Re-identificationY. Gong†, Z. Zhong, Y. Qu, Z. Luo, R. Ji, M. Jiang* · NeurIPS 2024
- Ask, Attend, Attack: An Effective Decision-Based Black-Box Targeted Attack for Image-to-Text ModelsQ. Zeng†, Z. Wang, Y. Cheung, M. Jiang* · NeurIPS 2024
- An Interpretable Approach to the Solutions of High-Dimensional Partial Differential EquationsL. Cao†, Y. Liu, Z. Wang, D. Xu, K. Ye, K. C. Tan, M. Jiang* · AAAI 2024
- Generating Diagnostic and Actionable Explanations for Fair Graph Neural NetworksZ. Wang†, Q. Zeng, W. Lin, M. Jiang, K. C. Tan · AAAI 2024
- Evolutionary Multitask Optimization with Lower Confidence Bound-Based Solution Selection StrategyZ. Wang†, L. Cao, L. Feng, M. Jiang*, K. C. Tan · IEEE TEVC
- Spatial-Temporal Knowledge Transfer for Dynamic Constrained Multiobjective OptimizationZ. Wang†, D. Xu, M. Jiang*, K. C. Tan · IEEE TEVC
- Multiview Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled DataZ. Wang†, Q. Zeng, W. Lin, M. Jiang, K. C. Tan · IEEE TNNLS
- An Efficient Dynamic Resource Allocation Framework for Evolutionary Bilevel OptimizationD. Xu†, K. Ye, Z. Zheng, T. Zhou, G. G. Yen, M. Jiang* · IEEE TCYB
- Learning-Based Directional Improvement Prediction for Dynamic Multiobjective OptimizationY. Ye, S. Liu, J. Zhou, Q. Lin, M. Jiang, K. C. Tan · IEEE TEVC
- Dynamic Multiobjective Evolutionary Optimization via Knowledge Transfer and MaintenanceQ. Lin, Y. Ye, L. Ma, M. Jiang, K. C. Tan · IEEE TSMC: Systems
- Transformer-Based Network with Temporal Depthwise Convolutions for sEMG RecognitionZ. Wang, J. Yao, M. Xu, M. Jiang, J. Su · Pattern Recognition
2023
- Robust Graph Meta-learning via Manifold Calibration with Proxy SubgraphsZ. Wang†, L. Cao, W. Lin, M. Jiang, K. C. Tan · AAAI 2023
- Improving Performance Insensitivity of Large-Scale Multiobjective Optimization via Monte Carlo Tree SearchH. Hong†, M. Jiang*, G. G. Yen · IEEE TCYB
- An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature SelectionL. Li, M. Xuan, Q. Lin, M. Jiang, Z. Ming, K. C. Tan · IEEE TEVC
- Dual-Stream Transformer with Distribution Alignment for Visible-Infrared Person Re-IdentificationZ. Chai, Y. Ling, Z. Luo, D. Lin, M. Jiang, S. Li · IEEE TCSVT
2022
- An Online Prediction Approach Based on Incremental Support Vector Machine for Dynamic Multiobjective OptimizationD. Xu†, M. Jiang*, W. Hu, S. Li, R. Pan, G. G. Yen · IEEE TEVC
- A Knowledge Guided Transfer Strategy for Evolutionary Dynamic Multiobjective OptimizationY. Guo, G. Chen, M. Jiang, D. Gong, J. Liang · IEEE TEVC
- Reducing Negative Transfer Learning via Clustering for Dynamic Multiobjective OptimizationJ. Li, T. Sun, Q. Lin, M. Jiang, K. C. Tan · IEEE TEVC
- WalkGAN: Network Representation Learning with Sequence-Based Generative Adversarial NetworksT. Jin, X. Yang, Z. Yu, H. Luo, Y. Zhang, F. Jie, X. Zeng, M. Jiang · IEEE TNNLS
- Fast Multilabel Feature Selection via Global Relevance and Redundancy OptimizationJ. Zhang, Y. Lin, M. Jiang, S. Li, Y. Tang, J. Long, J. Weng, K. C. Tan · IEEE TNNLS
- Learning from Weakly Labeled Data Based on Manifold Regularized Sparse ModelJ. Zhang, S. Li, M. Jiang, K. C. Tan · IEEE TCYB
2021
- Evolutionary Transfer Optimization — A New Frontier in Evolutionary Computation ResearchK. C. Tan, L. Feng, M. Jiang · IEEE Computational Intelligence Magazine2024 IEEE CIM 杰出论文奖
- Manifold Interpolation for Large-Scale Multiobjective Optimization via Generative Adversarial NetworksZ. Wang†, H. Hong, K. Ye, G. Zhang, M. Jiang*, K. C. Tan · IEEE TNNLS
- Knee Point-Based Imbalanced Transfer Learning for Dynamic Multiobjective OptimizationM. Jiang, Z. Wang, H. Hong, G. G. Yen · IEEE TEVC
- A Fast Dynamic Evolutionary Multiobjective Algorithm via Manifold Transfer LearningM. Jiang, Z. Wang, L. Qiu, S. Guo, X. Gao, K. C. Tan · IEEE TCYB
- Individual-Based Transfer Learning for Dynamic Multiobjective OptimizationM. Jiang, Z. Wang, S. Guo, X. Gao, K. C. Tan · IEEE TCYB
- Evolutionary Search with Multi-View Prediction for Dynamic Multi-Objective OptimizationW. Zhou, L. Feng, K. C. Tan, M. Jiang, Y. Liu · IEEE TEVC
- Graph-Based Class-Imbalance Learning with Label EnhancementG. Du, J. Zhang, M. Jiang, J. Long, Y. Lin, S. Li, K. C. Tan · IEEE TNNLS
- Inverse Gaussian Process Modeling for Evolutionary Dynamic Multiobjective OptimizationH. Zhang, J. Ding, M. Jiang, K. C. Tan, T. Chai · IEEE TCYB
- Monodirectional Tissue P Systems with PromotersB. Song, X. Zeng, M. Jiang, M. J. Pérez-Jiménez · IEEE TCYB
2017 – 2020
- Multi-label Feature Selection via Global Relevance and Redundancy OptimizationJ. Zhang, et al., M. Jiang · IJCAI 2020
- A Mixture-of-Experts Prediction Framework for Evolutionary Dynamic Multiobjective OptimizationR. Rambabu, P. Vadakkepat, K. C. Tan, M. Jiang · IEEE TCYB 2020
- Clustering Passenger Trip Data for the Potential Passenger Investigation and Line Design of Customized Commuter BusG. Qiu, R. Song, S. He, W. Xu, M. Jiang · IEEE TITS 2019
- Transfer Learning-Based Dynamic Multiobjective Optimization AlgorithmsM. Jiang*, Z. Huang, L. Qiu, W. Huang, G. G. Yen · IEEE TEVC 2018
- Integration of Global and Local Metrics for Domain Adaptation Learning via Dimensionality ReductionM. Jiang, W. Huang, Z. Huang, G. G. Yen · IEEE TCYB 2017
荣誉Honors
- 2024IEEE Computational Intelligence Magazine 杰出论文奖
- 2023–26全球前 2% 顶尖科学家（斯坦福大学 / 爱思唯尔）
- 2019吴文俊人工智能自然科学奖
- 2019Publons Top Peer Reviewer Award（计算机科学）
- 2016IEEE CIS Outstanding Chapter Award（厦门分会主席）
- 2016IEEE Transactions on Cybernetics 杰出审稿人奖
学术服务Service
- 主编IEEE CIM2026–
- 编委IEEE TEVC2023–
- 编委IEEE CIM2022–2025
- 编委IEEE TNNLS2020–2025
- 编委IEEE TCDS2018–2023, 2025
- 领域主席IJCAI · NeurIPS2024, 2026
- 客座编辑特刊 3 期2017, 2018, 2026
- 主席IEEE CIS 技术委员会2019–2020
- 创始主席IEEE CIS 厦门分会2013–
20132016201920222025
完整列表与更早的学术服务
- 2026–主编，IEEE Computational Intelligence Magazine
- 2023–编委，IEEE Transactions on Evolutionary Computation
- 2026领域主席，NeurIPS 2026
- 2026客座编辑，IEEE TEVC 特刊 Evolutionary Computation Meets Large Language Models
- 2024领域主席，IJCAI 2024
- 2022–25编委，IEEE Computational Intelligence Magazine
- 2020–25编委，IEEE Transactions on Neural Networks and Learning Systems
- 2018–25编委，IEEE Transactions on Cognitive and Developmental Systems
- 2019–20主席，IEEE CIS Intelligent Systems and Applications Technical Committee
- 2013–创始主席，IEEE CIS 厦门分会
- 首席客座编辑，IEEE Systems Journal 特刊 Human-like Intelligence and Robotics（2017）
- 客座编辑，International Journal of Distributed Sensor Networks 特刊 Advances in Industrial Wireless Sensor Networks（2018）
- 程序委员会主席，IEEE CIS 与厦门大学计算优化与学习暑期学校（2019）
- 组织委员会共同主席，ICACI 2018；宣传主席，IEEE WCCI 2016
- 专题会议组织者，IEEE WCCI 2016、ICIRA 2015（知识与技能迁移）
- 大会主席，MIND 2025
- 副主席，IEEE CIS 社交媒体分委会（2013–2018）；委员，IEEE CIS 分会分委会（2015–2017）
- 委员，IEEE CIS Emergent Technologies TC、Task Force on Towards Human-like Intelligence；CCF 理论计算机科学专委会
- 理事，福建省人工智能学会；
- 程序委员：AAAI、CEC、ICONIP、ISNN、ICACI、IEEE CIHLI、NCTCS 等（2011–2019）
招生Prospective Students
课题组招收硕士、博士研究生和博士后，也接收本科生参与科研。
- 研究方向
- 动态多目标优化、学习驱动的演化计算、大语言模型与优化、AI for Science 与可微仿真、面向工程决策的人工智能。
- 指导方式
- 入门阶段有定期组会和一对一讨论，对实验设计和论文写作给出细致反馈；随着能力增长，鼓励学生自主选题、独立负责项目。
- 背景要求
- 扎实的数学基础（线性代数、概率、微积分），熟练使用 Python 或 MATLAB，具备机器学习或演化计算的基础知识，能阅读英文文献。最重要的是好奇心、坚持和学术诚信。
- 联系方式
- 邮件标题请写“报考—姓名—硕士/博士/博士后”。正文请说明你的学校和专业、具体对哪项研究感兴趣，以及相关背景和科研经历，并附简历和成绩单。详见招生说明。