何东晓，天津大学智能与计算学部教授，博士生导师，国家自然科学基金优秀青年科学基金获得者。主要研究复杂图数据分析及其应用， 在ICML、IJCAI、NeurIPS、AAAI、WWW 等CCF A 类会议以及TKDE、TNNLS、TCYB 等IEEE Trans 上发表长文50余篇， 获数据挖掘顶会ICDM21最佳学生论文奖亚军、全国社会媒体处理大会SMP2022最佳论文奖、《自动化学报》年度优秀论文奖。 主持国家自然基金项目4项、国家重点研发课题1项。担任中科院一区SCI期刊Neural Networks编委， CCF A类会议NeurIPS 2024的Area Chair，以及AAAI2019, AAAI 2021, AAAI 2022, IJCAI2021等的Senior PC， 入选百度学术发布的AI华人女性青年学者。

Work Experiences (工作经历)

     · 2023年7月至今, 天津大学计算机科学与技术学院, 教授, 博士生导师

     · 2021年7月至2023年6月, 天津大学计算机科学与技术学院, 英才副教授(特聘研究员), 博士生导师

     · 2017年7月至2021年6月, 天津大学计算机科学与技术学院, 副教授

     · 2014年7月至2017年6月, 天津大学计算机科学与技术学院, 讲师

     · 中国人工智能学会人工智能基础专委会委员

     · 中国人工智能学会智能服务专委会委员

     · 中国中文信息学会社会媒体处理专委会委员

     · 中科院一区SCI期刊Neural Networks编委

     · Area Chair of NeurIPS-24

     · Senior PC of AAAI-19, AAAI-21, IJCAI-21, AAAI-22

     · 2019.09~2020.08: Visiting Scholar at the University of Illinois at Chicago

                                     美国伊利诺伊大学芝加哥分校 访问学者

     · 2014.12~2015.08: Post-Doc Researcher in Department of Computer Science, Dresden University of Technology, Germany

                                     博士后, 德国德累斯顿工业大学, 计算机科学与工程系

     · 2012.09~2013.10: Visiting PhD student in Department of Computer Science & Engineering, Washington University in Saint Louis, Missouri, USA

                                     联合培养博士研究生, 美国圣路易斯华盛顿大学, 计算机科学与工程系 

     · 2010.09~2014.06: PhD in College of Computer Science and Technology, Jilin University, China

                               博士, 吉林大学, 计算机科学与技术学院, 计算机应用技术专业 

     · 2007.09~2010.07: MS in College of Computer Science and Technology, Jilin University, China

                                     硕士, 吉林大学, 计算机科学与技术学院, 计算机应用技术专业 

     · 2003.09~2007.07: BS in College of Computer Science and Technology, Jilin University, China

                                     学士, 吉林大学, 计算机科学与技术学院, 计算机科学与技术专业

     · 1. 国家自然科学基金优秀青年科学基金, 主持

     · 2. 国家重点研发计划课题"基于多因子数据时空关联的社会治理要素风险动态感知与分析技术", 起止时间: 2023.11 - 2026.10, 项目经费: 615万(国拨265万+省拨150万+自筹200万), 主持

     · 3. 国家自然科学基金面上项目"真实复杂场景下图神经网络关键问题研究" (批准号: 62276187), 起止时间: 2023.01 - 2026.12, 直接项目经费: 55万, 主持, 在研

     · 4. 国家自然科学基金面上项目"基于马尔可夫随机场的大规模网络社团发现研究" (批准号: 61876128), 起止时间: 2019.01 - 2022.12, 直接项目经费: 62万, 主持, 已结项

     · 5. 国家自然科学基金项目"融合网络拓扑与结点、链接属性的重叠社区发现方法研究" (批准号: 61502334), 起止时间: 2016.01 - 2018.12, 项目经费: 23.65万, 主持, 已结项

2023:

[1] Dongxiao He, Jitao Zhao, Rui Guo, Di Jin, Zhiyong Feng, Yuxiao Huang, Weixiong Zhang, Zhen Wang, Contrastive Learning Meets Homophily: Two Birds with One Stone, (ICML-23), 2023: 12775-12789 (CCF-A类会议长文) , Oral

[2] Dongxiao He, Tao Wang, Lu Zhai, Di Jin, Liang Yang, Yuxiao Huang, Zhiyong Feng & Philip S. Yu, Adversarial Representation Mechanism Learning for Network Embedding, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 35(2): 1200-1213. (CCF-A类期刊)

[3] Di Jin, Zhizhi Yu, Dongxiao He*, Carl Yang, Philip S. Yu & Jiawei Han, GCN for HIN via Implicit Utilization of Attention and Meta-paths, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 35(4): 3925-3937. (CCF-A类期刊)

[4] Di Jin, Zhizhi Yu, Pengfei Jiao*, Shirui Pan, Dongxiao He*, Jia Wu, Philip S. Yu & Weixiong Zhang, A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 35(2): 1149-1170. (CCF-A类期刊)

[5] Liang Yang, Qiuliang Zhang, Chuan Wang, Xiaochun Cao, Bingxin Niu, Runjie Shi, Wenmiao Zhou, Dongxiao He*, Yuanfang Guo* & Zhen Wang, Graph Neural Network without Propagation, The Web Conference (WWW-23), 2023: 469-477. (CCF-A类会议长文)

[6] Cuiying Huo, Di Jin, Yawen Li, Dongxiao He*, Yu-Bin Yang & Lingfei Wu, T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation, Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23), 2023: 4339-4346. (CCF-A类会议长文)

[7] Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He*, Xiao Wang, Hanghang Tong & Jiawei Han, Embedding Text-Rich Graph Neural Networks with Sequence and Topical Semantic Structures, Knowledge and Information Systems (KAIS), 2023, 65(2): 613-640. (CCF-B类期刊)

 

2022:

[1] Dongxiao He, Huixin Liu, Zhiyong Feng, Xiaobao Wang, Di Jin, Wenze Song & Yuxiao Huang, A Joint Community Detection Model: Integrating Directed and Undirected Probabilistic Graphical Models via Factor Graph with Attention Mechanism, IEEE Transactions on Big Data (TBD), 2022, 8(4): 994-1006. (IEEE汇刊, 中科院二区SCI期刊) 获全国社会媒体大会SMP2022最佳论文奖, 推荐至TBD期刊

[2] Dongxiao He, Rui Guo, Xiaobao Wang, Di Jin, Yuxiao Huang & Wenjun Wang, Inflation Improves Graph Learning, The Web Conference (WWW-22), 2022, pp. 1466-1474. (CCF-A类会议长文)

[3] Dongxiao He, Chundong Liang, Huixin Liu, Mingxiang Wen, Pengfei Jiao & Zhiyong Feng, Block Modeling-Guided Graph Convolutional Neural Networks, Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022, pp. 4022-4029. (CCF-A类会议长文)

[4] Dongxiao He, Chundong Liang, Cuiying Huo, Zhiyong Feng, Di Jin, Liang Yang & Weixiong Zhang, Analyzing Heterogeneous Networks with Missing Attributes by Unsupervised Contrastive Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022, DOI: 10.1109/TNNLS.2022.3149997. (中科院一区SCI期刊)

[5] Dongxiao He, Youyou Wang, Jinxin Cao, Weiping Ding, Shizhan Chen, Zhiyong Feng, Bo Wang & Yuxiao Huang, A Network Embedding-Enhanced Bayesian Model for Generalized Community Detection in Complex Networks, Information Sciences, 2021, pp. 306-322. (中科院一区SCI期刊)

[6] Liang Yang, Wenmiao Zhou, Weihang Peng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao & Dongxiao He*, Graph Neural Networks Beyond Compromise Between Attribute and Topology, The Web Conference (WWW-22), 2022, pp. 1127-1135. (CCF-A类会议长文)

[7] Tao Wang, Di Jin, Rui Wang, Dongxiao He*& Yuxiao Huang, Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily, Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022, pp. 4210-4218. (CCF-A类会议长文)

[8] Di Jin, Rui Wang, Meng Ge*, Dongxiao He*, Xiang Li, Wei Lin & Weixiong Zhang, RAW-GNN: RAndom Walk Aggregation based Graph Neural Network, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22), 2022, pp. 2108-2114. (CCF-A类会议长文)

[9] Pengfei Jiao, Xuan Guo, Xin Jing, Dongxiao He*, Huaming Wu, Shirui Pan, Maoguo Gong & Wenjun Wang, Temporal Network Embedding for Link Prediction via VAE Joint Attention Mechanism, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022, 33(12): 7400-7413. (中科院一区SCI期刊)

[10] Liang Yang, Weihang Peng, Wenmiao Zhou, Bingxin Niu, Junhua Gu, Chuan Wang, Yuanfang Guo, Dongxiao He & Xiaochun Cao, Difference Residual Graph Neural Networks, Proceedings of the Thirtieth ACM International Conference on Multimedia (MM-22), 2022, pp. 3356-3364. (CCF-A类会议长文)

[11] Liang Yang, Cheng Chen, Weixun Li, Bingxin Niu, Junhua Gu, Chuan Wang, Dongxiao He, Yuanfang Guo & Xiaochun Cao, Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing, Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022, pp. 4327-4336. (CCF-A类会议长文)

[12] Pengfei Jiao, Tianpeng Li, Huaming Wu, Chang-Dong Wang, Dongxiao He & Wenjun Wang, HB-DSBM: Modeling the Dynamic Complex Networks From Community Level to Node Level, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022, DOI: 10.1109/TNNLS.2022.3149285 (中科院一区SCI期刊)

[13] Di Jin, Rui Wang, Tao Wang, Dongxiao He, Weiping Ding, Yuxiao Huang, Longbiao Wang & Witold Pedrycz, Amer: A New Attribute-Missing Network Embedding Approach. IEEE Transactions on Cybernetics (TCYB), 2022, DOI: 10.1109/TCYB.2022.3166539. (中科院一区SCI期刊)

[14] Dongxiao He, Yanli Wu, Youyou Wang, Zhizhi Yu, Zhiyong Feng, Xiaobao Wang & Yuxiao Huang, Identification of Communities with Multi-Semantics via Bayesian Generative Model, IEEE Transactions on Big Data (TBD), 2022, 8(4): 869-881. (IEEE汇刊，中科院二区SCI期刊)

 

2021:

[1] Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He*, Xiao Wang*, Hanghang Tong & Jiawei Han, AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks, IEEE International Conference on Data Mining (ICDM-21), 2021, pp. 837-846. Best Student Paper Award Runner-Up (最佳学生论文奖亚军)

[2] Dongxiao He, Shuai Li, Di Jin, Pengfei Jiao & Yuxiao Huang, Self-Guided Community Detection on Networks with Missing Edges. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), 2021, pp. 3508-3514. (CCF-A类会议长文)

[3] Dongxiao He, Youyou Wang, Jinxin Cao, Weiping Ding, Shizhan Chen, Zhiyong Feng, Bo Wang & Yuxiao Huang, A Network Embedding-Enhanced Bayesian Model for Generalized Community Detection in Complex Networks, Information Sciences, 2021, pp. 306-322. (中科院一区SCI期刊)

[4] Pengfei Jiao, Tianpeng Li, Yingjie Xie, Yinghui Wang, Wenjun Wang, Dongxiao He*& Huaming Wu, Generative Evolutionary Anomaly Detection in Dynamic Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, DOI: 10.1109/TKDE.2021.3129057. (CCF-A类期刊)

[5] Di Jin, Xiaobao Wang, Dongxiao He, Jianwu Dang & Weixiong Zhang, Robust Detection of Link Communities with Summary Description in Social Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021, pp. 2737-2749. (CCF-A类期刊)

[6] Di Jin, Zhizhi Yu, Cuiying Huo, Dongxiao He, Xiao Wang & Jiawei Han, Universal Graph Convolutional Networks, The Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS-21), 2021, pp. 10654-10664. (CCF-A类会议长文)

[7] Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li & Philip S Yu, Htcinfomax: A Global Model for Hierarchical Text Classification via Information Maximization, Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT-21), 2021, pp.3259–3265.

 

2020:

[1] Dongxiao He, Yue Song, Di Jin, Zhiyong Feng, Binbin Zhang, Zhizhi Yu & Weixiong Zhang, Community-Centric Graph Convolutional Network for Unsupervised Community Detection, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), 2020, pp. 3515-3521. (CCF-A类会议长文)

[2] Dongxiao He, Lu Zhai, Zhigang Li, Liang Yang, Di Jin, Yuxiao Huang & Philip S. Yu, Adversarial Mutual Information Learning for Network Embedding, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), 2020, pp. 3321-3327. (CCF-A类会议长文)

[3] Di Jin, Ge Zhang, Kunzeng Wang, Pengfei Jiao, Dongxiao He, Francoise Fogelman-Soulié & Xin Huang, Detecting Communities with Multiplex Semantics by Distinguishing Background, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020, 32(11): 2144-2158. (CCF-A类期刊)

[4] Di Jin, Xiaobao Wang, Dongxiao He, Jianwu Dang and Weixiong Zhang, Robust Detection of Link Communities with Summary Description in Social Networks, TKDE, 2020 (CCF-A类期刊)

[5] Di Jin, Bingyi Li, Pengfei Jiao, Dongxiao He & Weixiong Zhang, Modeling with Node Popularities for Autonomous Overlapping Community Detection, ACM Transactions on Intelligent Systems and Technology (TIST), 2020, 11(3): 1-23. (ACM汇刊, 中科院三区SCI期刊)

[6] Di Jin, Binbin Zhang, Yue Song, Dongxiao He, ModMRF: A Modularity-based Markov Random Field Method for Community Detection, Neurocomputing, 2020  

[7] Di Jin, Jing He, Bianfang Chai, Dongxiao He, Semi-Supervised Community Detection on Attributed Networks using Non-Negative Matrix Tri-Factorization with Node Popularity, Frontiers of Computer Science, 2020  

 

2019:

[1] Dongxiao He, Wenze Song, Di Jin, Zhiyong Feng & Yuxiao Huang, An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 2019, pp. 5730-5736. (CCF-A类会议长文), Oral

[2] Di Jin, Bingyi Li, Pengfei Jiao, Dongxiao He & Weixiong Zhang, Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 2019, pp. 2663-2669. (CCF-A类会议长文), Oral

[3] Di Jin, Xinxin You, Weihao Li, Dongxiao He, Peng Cui, Françoise Fogelman-Soulié & Tanmoy Chakraborty, Incorporating Network Embedding into Markov Random Field for Better community detection, Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 2019, pp. 160–167. (CCF-A类会议长文), Oral

[4] Di Jin, Ziyang Liu, Weihao Li, Dongxiao He & Weixiong Zhang, Graph Convolutional Network Meets Markov Random Field: Semi-Supervised Community Detection in Attribute Networks, Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 2019, pp. 152–159. (CCF-A类会议长文), Oral

[5] Di Jin, Jiantao Huang, Pengfei Jiao, Liang Yang, Dongxiao He, Françoise Soulie-Fogelman & Yuxiao Huang, A Novel Generative Topic Embedding Model by Introducing Network Communities, The Web Conference (WWW-19), 2019, pp. 2886–2892. (CCF-A类会议短文)

[6] Xiaobao Wang, Di Jin, Mengquan Liu, Dongxiao He, Kaska Musial-Gabrys & Jianwu Dang, Emotional Contagion-Based Social Sentiment Mining in Social Networks by Introducing Network Communities, ACM International Conference on Information and Knowledge Management (CIKM-19), 2019, pp. 1763–1772. (CCF-B类会议长文), Oral

[7] Di Jin, Bingyi Li, Pengfei Jiao, Dongxiao He, and Hongyu Shan. Community Detection via Joint Graph Convolutional Network Embedding in Attribute Network. In International Conference on Artificial Neural Networks, Springer, ICANN-19. (CCF-C类会议长文)

[8] 金弟, 尤心心, 刘岳森, 何东晓*. 结构特征强化的高效马尔可夫随机场社团发现方法. 计算机学报, 2019, 42(12): 2821-2835. (CCF汇刊，中文A类期刊)

 

2018 :

[1] Dongxiao He, Xinxin You, Zhiyong Feng, Di Jin, Xue Yang, Weixiong Zhang. A Network-Specific Markov Random Field Approach to Community Detection, AAAI-18 (CCF-A类会议长文), Oral

[2] Di Jin, Xiaobao Wang, Ruifang He, Dongxiao He, Weixiong Zhang. Robust Detection of Link Communities in Large Social Networks by Exploiting Link Semantics, AAAI-18 (CCF-A类会议长文), Oral

[3] Di Jin, Meng Ge, Liang Yang, Longbiao Wang, Dongxiao He, Weixiong Zhang, Integrative Network Embedding via Deep Joint Reconstruction, IJCAI-18 (CCF-A类会议长文), Oral

[4] Dongxiao He, Xue Yang, Zhiyong Feng, Shizhan Chen, Keman Huang, Zhenzhu Wang, A Probabilistic Model for Service Clustering – Jointly Using Service Invoation and Service Characteristics, ICWS-18 (CCF-B类会议)

[5] 金弟, 刘子扬, 贺瑞芳, 王啸, 何东晓, 面向带属性复杂网络的鲁棒、强解释性社团发现方法, 计算机学报, 2018

   

2017:

[1] Dongxiao He, Zhiyong Feng, Di Jin, Xiaobao Wang, Weixiong Zhang, Joint Identification of Network Communities and Semantics via Integrative Modeling of Network Topologies and Node Contents, AAAI-17 (CCF-A类会议长文)

[2] Xiao Liu, Wenjun Wang, Dongxiao He*, Pengfei Jiao, Di Jin, Carlo Vittorio Cannistraci, Semi-supervised community detection based on non-negative matrix factorization with node popularity, Information Sciences, Volume 381, March 2017, Pages 304-321 (SCI, IF: 3.858 )

 

2016:

[1] Liang Yang, Xiaochun Cao, Dongxiao He*, Chuan Wang, Xiao Wang, Weixiong Zhang. Modularity based community detection with deep learning. IJCAI-16, pp 2252-2258. (CCF-A类会议长文), Full Oral

[2] Di Jin, Hongcui Wang, Dongxiao He, Weixiong Zhang. Detect overlapping communities via modeling and ranking node popularities. AAAI-16, pp.172-178  (CCF-A类会议长文)

 

2015 and before:

[1] Dongxiao He, Dayou Liu, Di Jin, Weixiong Zhang. A stochastic model for the detection of heterogeneous link communities in complex networks, AAAI-15, Jan 25-30, 2015 (CCF-A类会议长文), Oral

[2] 何东晓, 周栩, 王佐, 周春光, 王喆, 金弟. 复杂网络社区挖掘 — 基于聚类融合的遗传算法[J]. 自动化学报, 2010, 36(8): 1160-1170. (国家权威期刊, EI检索号: 20103613222062) 该论文获2012年度 《自动化学报》优秀论文奖(共3篇优秀论文)，依据《自动化学报》公布的数据截止到2012年10月23日该论文在该学报2010和2011年度的所有非综述类论文中被引用次数最高，排第一名