李明
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李明，教授，博士生导师，浙江省高校高层次拔尖人才 (第二批“浙江省高校领军人才计划”培养人选，即“5246人才工程”)，浙江省“钱江人才计划”紧缺急需人才（仅限海归博士），入选意大利ICTP研究中心高级访问学者计划。浙师大“双龙学者”特聘教授，现任浙江全省智能教育技术与应用重点实验室副主任，中国人工智能学会、中国计算机学会会员，中国人工智能学会知识工程与分布智能专委会委员，中国人工智能学会机器学习专业委员会通讯委员，CCF-AI专委会图机器学习学组首届秘书处成员，目前担任权威期刊Neural Networks在内的七个国际期刊副主编/编委，曾任IEEE Transactions on Neural Networks and Learning Systems期刊“Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications” 专刊首席特邀副主编。在国际权威期刊如IEEE TPAMI、Artificial Intelligence、IEEE TKDE、IEEE TNNLS、IEEE TCYB及 CCF-A 类会议 ICML、NeurIPS、IJCAI、AAAI、ICDE上发表论文100余篇（含8篇ESI高被引、2篇ESI热点论文），Google学术引用接近4500次，h-index: 33，入选全球前2%顶尖科学家榜单，常年担任ICML、NeurIPS、IJCAI、KDD、ICLR等国际会议的PC Member及IEEE TPAMI、IEEE TKDE、IEEE TNNLS、IEEE TCYB等权威期刊的审稿人，近年来多次主持或应邀参加“图神经网络”、“图机器学习”等方向学术论坛，及CCF/CAAI专委会走进高校活动。主持国家自然科学基金面上项目1项、青年项目1项、浙江省“尖兵”“领雁”科技计划项目（即省重点研发计划项目）1项；作为合作单位项目负责人联合承担国家自然科学基金区域创新发展联合基金重点项目1项；作为核心成员参与国家科技创新2030—“新一代人工智能”重大项目课题1项、浙江省重点研发计划项目2 项。 目前已申请发明专利20余项，相关图神经网络技术成果已在知识追踪、学习行为分析等智能教育场景中实现技术落地，并成功应用于科大讯飞多个智能教育平台服务中，产生了良好的经济效益与示范效应。 其中，专利成果《基于图卷积的知识追踪、数据处理方法、系统和存储介质》荣获第二十五届中国专利优秀奖。
详见其个人主页：https://mingli-ai.github.io/
🔆 图神经网络、图表示学习、超图表示学习、几何深度学习等方向的代表作（含CCF/CAA/CAAI推荐A类期刊/会议35篇, ESI高被引/热点🏆5篇）：
● Are graph convolutional networks with random weights feasible? ESI Highly Cited Paper 🏆 (CCF/CAAI-A类, CAA-A+期刊)
C. Huang, M. Li*, F. Cao, H. Fujita, Z. Li, X. Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 3, pp. 2751-2768, 2023.
● Multi-view graph convolutional networks with attention mechanism [code] (CCF/CAA/CAAI-A类期刊)
K. Yao, J. Liang, J. Liang, M. Li, F. Cao
Artificial Intelligence, vol. 307, 103708, 2022.
● AEGK: Aligned Entropic Graph Kernels through continuous-time quantum walks (CCF/CAA/CAAI-A类期刊)
L. Bai, L. Cui, M. Li, P. Ren, Y. Wang, Y. Philip, L. Zhang, E. Hancock
IEEE Transactions on Knowledge and Data Engineering, vol. 37, no. 3, pp. 1064-1078, 2025.
● HAQJSK: Hierarchical-aligned quantum Jensen-Shannon kernels for graph classification ESI Hot Paper 🏆 (CCF/CAA-CAAI-A类期刊)
L. Bai, L. Cui, Y. Wang, M. Li*, J. Li, P. Yu, E. Hancock
IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 11, pp. 6370-6384, 2024.
● Collaborative knowledge graph fusion by exploiting the open corpus (CCF/CAA/CAAI-A类期刊)
Y. Wang, Y. Wan, L. Bai, L. Cui, Z. Xu, M. Li, P. Yu, E. Hancock
IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 2, pp. 475-489, 2024.
● EduCross: Dual adversarial bipartite hypergraph learning for cross-modal retrieval in multimodal educational slides (CAA-A+类期刊, CAAI A类期刊)
M. Li, S. Zhou, Y. Chen, C. Huang, Y. Jiang*
Information Fusion, vol. 109, 102428, 2024.
● Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction ESI Highly Cited Paper 🏆 (CAA-A+类期刊, CAAI-A类期刊)
M. Li, X. Zhuang, L. Bai, W. Ding
Information Fusion, vol. 105, 102224, 2024.
● When hypergraph meets heterophily: New benchmark datasets and baseline (CCF/CAA/CAAI-A类会议)
M. Li, Y. Gu, Y. Wang, Y. Fang, Lu Bai, X. Zhuang, P. Lio
AAAI, 2025.
● Deep hypergraph neural networks with tight framelets (CCF/CAA/CAAI-A类会议)
M. Li, Y. Fang, Y. Wang, H. Feng, Y. Gu, L. Bai, P. Lio
AAAI, 2025.
● DHAKR: Learning deep hierarchical attention-based kernelized representations for graph classification (CCF/CAA/CAAI-A类会议)
F. Qian, L. Bai*, L. Cui, M. Li*, Z. Lyu, H. Du, E. Hancock
AAAI, 2025.
● ML-GOOD: Towards multi-label graph out-of-distribution detection (CCF/CAA/CAAI-A类会议)
T. Cai, Y. Jiang, M. Li, C. Huang, Y. Wang, Q. Huang
AAAI, 2025.
● Path integral based convolution and pooling for graph neural networks [code] [PyG Implementation] (CCF/CAA/CAAI-A类会议)
Z. Ma, J. Xuan, Y. G. Wang, M. Li, P. Lio
NeurIPS, 2020, pp. 16421-16433.
● HC-GAE: The hierarchical cluster-based graph auto-encoder for graph representation learning (CCF/CAA/CAAI-A类会议)
Z. Xu, L. Bai, L. Cui, M. Li, Y. Wang, E. R. Hancock
NeurIPS, 2024, accept.
● Long-range brain graph transformer (CCF/CAA/CAAI-A类会议)
S. Yu, S. Jin, M. Li, T. Sarwar, F. Xia
NeurIPS, 2024, accept.
● How universal polynomial bases enhance spectral graph neural networks: Heterophily, over-smoothing, and over-squashing [link][code] (CCF/CAA/CAAI-A类会议)
K. Huang*, Y. G. Wang, M. Li*, P. Lio
ICML, 2024, pp. 20310-20330.
● QBMK: Quantum-based matching kernels for un-attributed graphs [link] (CCF/CAA/CAAI-A类会议)
L. Bai, L. Cui, M. Li, Y. Wang, E. Hancock
ICML, 2024, pp. 2364-2374. (Spotlight Paper: 3.5% acceptance rate)
● Haar graph pooling [link][code] (CCF/CAA/CAAI-A类会议)
Y. G. Wang, M. Li*, Z. Ma, G. Montufar, X. Zhuang, Y. Fan
ICML, 2020, pp. 9952-9962.
● How framelets enhance graph neural networks [link] [code] (CCF/CAA/CAAI-A类会议)
X. Zheng, B. Zhou, J. Gao, Y. G. Wang, P. Lio, M. Li, G. Montufar
ICML, 2021, pp. 12761-12771. (Spotlight Paper)
● How powerful are shallow neural networks with bandlimited random weights? (CCF/CAA/CAAI-A类会议)
M. Li, S. Sonoda, F. Cao, Y. G. Wang, J. Liang
ICML, 2023, pp. 19960-19981.
● Stability and generalization of ℓp-regularized stochastic learning for GCN (CCF/CAA/CAAI-A类会议)
S. Lv, S. Liu, L. Wei, M. Li
IJCAI, 2023, pp. 5685-5693.
● Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications [link] ESI Highly Cited Paper 🏆 (CAA/CAAI-A类期刊, CCF-B类期刊)
M. Li*, A. Micheli, Y. G. Wang, S. Pan, P. Lio, G. Gnecco, M. Sanguineti
IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 4, pp. 4367-4372, 2024.
● Permutaion equivariant graph framelets for heterophilous graph learning [code] ESI Highly Cited Paper 🏆(CAA/CAAI-A类期刊, CCF-B类期刊)
J. Li, R. Zheng, F. Han, M. Li*, X. Zhuang*
IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 9, pp. 11634-11648, 2024.
● Towards graph self-supervised learning with contrastive adjusted zooming (CAA/CAAI-A类期刊, CCF-B类期刊)
Y. Zheng, M. Jin, S. Pan, Y. F. Li, H. Peng, M. Li, Z. Li
IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 7, pp. 8882-8896, 2024.
● Flow2GNN: Flexible two-way flow message passing for enhancing GNNs beyond homophily (CAA/CAAI-A类期刊, CCF-B类期刊)
C. Huang, Y. Wang, Y. Jiang, M. Li, X. Huang, S. Wang, S. Pan, C. Zhou
IEEE Transactions on Cybernetics, vol. 54, no. 11, pp. 6607-6618, 2024.
● Correlation information enhanced graph anomaly detection via hypergraph transformation (CAA/CAAI-A类期刊, CCF-B类期刊)
C. Huang, C. Gao, M. Li, Y. Li, X. Wang, Y. Jiang, X. Huang
IEEE Transactions on Cybernetics, 2025.
● A unified framework for exploratory learning-aided community detection under topological uncertainty
Y. Hou, C. Tran, M. Li, W. Shin
IEEE Transactions on Network Science and Engineering, 2025.
● A simple yet effective framelet-based graph neural network for directed graphs [code] (CAAI-B类期刊)
C. Zou, A. Han, L. Lin, M. Li, J. Gao
IEEE Transactions on Artificial Intelligence, vol. 5, no. 4, pp. 1647-1657, 2024.
● Multiple pedestrian tracking with graph attention map on urban road scene (CAA-A类期刊, CCF/CAAI-B类期刊)
Z. Wang, Z. Li, J. Leng, M. Li*, L. Bai
IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 8, pp. 8567-8579, 2023.
● GoLoG: Global-to-local decoupling graph network with joint optimization for hyperspectral image classification (CAA/CAAI-A类期刊, CCF-B类期刊)
B. Yang, H. Ye, M. Li*, F. Cao, S. Pan
IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 5528014, 2023.
● Fast Haar transforms for graph neural networks (CAA-A类期刊, CCF/CAAI-B类期刊)
M. Li, Z. Ma, Y. G. Wang, X. Zhuang
Neural Networks, vol. 128, pp. 188-198, 2020.
● Embedding graphs on Grassmann manifold [code] (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
B. Zhou, X. Zheng, Y. G. Wang, M. Li, J. Gao
Neural Networks, vol. 152, pp. 322-331, 2022.
● Revisiting graph neural networks from hybrid regularized graph signal reconstruction (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
J. Miao, F. Cao, H. Ye, M. Li, B. Yang
Neural Networks, vol. 157, pp. 444-459, 2023.
● FrameERC: Framelet transform based multimodal graph neural networks for emotion recognition in conversation (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
M. Li, J. Shi, L. Bai, C. Huang, Y. Jiang, K. Lv, S. Wang, E. Hancock
Pattern Recognition, 2025.
● Collaborative graph neural networks for augmented graphs: A local-to-global perspective (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
Q. Guo, X. Yang, M. Li, Y. Qian
Pattern Recognition, vol. 158, 111020, 2025.
● QBER: Quantum-based entropic representations for un-attributed graphs (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
L. Cui, M. Li, L. Bai, Y. Wang, J. Li, Y. Wang, Z. Li, Y. Chen, E. Hancock
Pattern Recognition, vol. 145, 109877, 2024.
● AG-Meta: Adaptive graph meta learning via representation consistency over local subgraphs (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
Y. Wang, C. Huang, M. Li, Q. Huang, X. Wu, J. Wu
Pattern Recognition, vol. 151, 110387, 2024.
● BLoG: Bootstrapped graph representation learning with local and global regularization for recommendation (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
M. Li, L. Zhang, L. Cui, L. Bai, Z. Li, X. Wu
Pattern Recognition, vol. 144, 109874, 2023.
● Triplet teaching graph contrastive networks with self-evolving adaptive augmentation [code] (CAA/CAAI-A类期刊, CCF/CAAI-B类期刊)
J. Miao, F. Cao, M. Li, B. Yang, H. Ye
Pattern Recognition, vol. 142, 109687, 2023.
🔆 AI赋能教育技术与应用(交叉)方向代表作：
● EduCross: Dual adversarial bipartite hypergraph learning for cross-modal retrieval in multimodal educational slides
M. Li, S. Zhou, Y. Chen, C. Huang, Y. Jiang*
Information Fusion, vol. 109, 102428, 2024.
● Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction
ESI Highly Cited Paper 🏆
M. Li, X. Zhuang, L. Bai, W. Ding*
Information Fusion, vol. 105, 102224, 2024.
● EduGraph: Learning path-based hypergraph neural networks for MOOC course recommendation
M. Li, Z. Li*, C. Huang*, Y. Jiang, X. Wu
IEEE Transactions on Big Data, vol. 10, no. 6, pp. 706-719, 2024.
● Framelet based dual hypergraph neural networks for student engagement prediction [poster] [Best Short Paper Award]
M. Li*, J. Shi
AI4ED-AAAI, 2024, accept. Best Short Paper Award 🏆
🔆 教育技术学实证研究方向代表作：
● From motivational experience to creative writing: A motivational AR-based learning approach to promoting Chinese writing performance and positive writing behaviours
M. Li, Y. Chen, C. Huang, G. Hwang, M. Cukurova
Computers & Education, vol. 202, 104844, 2023. (SSCI&SCI，中科院一区TOP，影响因子: 8.9，教育学全球TOP1期刊) ▪ Journal Citation Reports (Clarivate, 2023): 1/269 (Education & Educational Research (Social Science))
● Incorporation of peer-feedback into the pedagogical use of spherical video-based virtual reality in writing education ESI Highly Cited Paper 🏆
Y. Chen, M. Li*, M. Cukurova, M. Jong
British Journal of Educational Technology, vol. 55, no. 5, pp. 519-540, 2024. (SSCI，中科院一区TOP，影响因子: 6.7，教育技术学国际顶级期刊) ▪ 12/269 (Education & Educational Research (Social Science))
● Promoting deep writing with immersive technologies: An SVVR‐supported Chinese composition writing approach for primary schools
Y. Chen, M. Li*, C. Huang, Z. Han, G. Hwang, G. Yang
British Journal of Educational Technology, vol. 53, no. 6, pp. 2071-2091, 2022. (SSCI，中科院一区TOP，影响因子: 6.7，教育技术学国际顶级期刊)
● Unleashing imagination: An effective pedagogical approach to integrate into spherical video-based virtual reality to improve students' creative writing
Y. Chen, M. Li*, M. Cukurova
Education and Information Technologies, vol. 29, pp. 6499-6523, 2024. (SSCI，中科院二区TOP，影响因子: 4.8)
● A systematic review of research on immersive technology-enhanced writing education: The current state and a research agenda
Y. Chen, M. Li*, C. Huang, M. Cukurova, Q. Ma
IEEE Transactions on Learning Technologies, vol. 17, pp. 919-938, 2024. (SSCI&SCI，影响因子: 2.9)
🔆 学术活动及相关服务
● 国际权威期刊副主编(Associate Editor)、编委(Editorial Board Member)：
▪ Neural Networks 副主编
▪ Applied Intelligence 副主编
▪ Alexandria Engineering Journal 副主编
▪ Network: Computation in Neural Systems 副主编
▪ Soft Computing 副主编
▪ Neural Processing Letters 副主编
▪ Education and Information Technologies 编委
● 中国计算机协会 (China Computer Federation，CCF) 会员
● 中国人工智能学会 (Chinese Association for Artificial Intelligence，CAAI) 会员
● 中国人工智能学会——机器学习专委会通讯委员
● 中国人工智能学会——知识工程与分布智能专委会委员
● The Institute of Electrical and Electronics Engineers (IEEE) 会员
● Australian Mathematical Society (AusMS), 澳大利亚数学会会员
● SPC Member for IJCAI (2025)
● PC Members for AAAI (2022/2025)、ICML (2020-2025), NeurIPS (2020-2025), ICLR (2022-2024)、IJCAI（2023/2024)、LoG (2022-2024)、KDD (2022/2024/2025)、WSDM (2022-2025)、ICASSP (2023/2025)、AJCAI (2021)、NCIIP (2021/2023)
● 期刊审稿人(审稿篇数400+)
▪ IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 23.6)
▪ IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 10.4)
▪ IEEE Transactions on Cybernetics (Outstanding Reviewer in 2016 and 2017) (Impact Factor: 11.8)
▪ IEEE Transactions on Knowledge and Data Engineering (Impact Factor: 8.9)
▪ IEEE Transactions on Intelligent Transportation Systems (Impact Factor: 8.5)
▪ IEEE Journal on Selected Areas in Communications (Impact Factor: 16.4)
▪ IEEE Transactions on Big Data (Impact Factor: 7.2)
▪ IEEE Journal of Selected Topics in Signal Processing (Impact Factor: 7.5)
▪ IEEE Transactions on Affective Computing (Impact Factor: 11.2)
▪ IEEE Computational Intelligence Magazine (Impact Factor: 9.0)
▪ IEEE Transactions on Emerging Topics in Computational Intelligence (Impact Factor: 5.5)
▪ IEEE Transactions on Network Science and Engineering (Impact Factor: 6.6)
▪ IEEE Transactions on Neural Systems & Rehabilitation Engineering (Impact Factor: 4.9)
▪ IEEE Transactions Services Computing (Impact Factor: 8.1)
▪ IEEE Transactions Software Engineering (Impact Factor: 7.4)
▪ IEEE Transactions on Mobile Computing (Impact Factor: 7.9)
▪ IEEE Intelligent Systems (Impact Factor: 6.4)
▪ IEEE Signal Processing Letters (Impact Factor: 3.9)
▪ IEEE Transactions on Artificial Intelligence
▪ IEEE/CAA Journal of Automatica Sinica (Impact Factor: 11.8)
▪ ACM Transactions on Knowledge Discovery from Data (Impact Factor: 4.4)
▪ Artificial Intelligence Review (Impact Factor: 12.0)
▪ SCIENCE CHINA Information Sciences (Impact Factor: 8.8)
▪ Neural Networks (Impact Factor: 7.8)
▪ Pattern Recognition (Impact Factor: 8)
▪ Neurocomputing (Impact Factor: 6.0)
▪ Information Sciences (Impact Factor: 8.1)
▪ Expert Systems with Applications (Impact Factor: 8.5)
▪ Knowledge-Based Systems (Impact Factor: 8.8)
▪ Applied Intelligence (Impact Factor: 5.3)
▪ Applied Soft Computing (Impact Factor: 8.7)
▪ Soft Computing (Impact Factor: 4.1)
▪ International Journal of Machine Learning and Cybernetics (Impact Factor: 5.6)
▪ British Journal of Educational Technology (Impact Factor:：6.6)
▪ Education and Information Technologies (Impact Factor:：5.5)
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