Minglai Shao (邵明来), Ph.D., 博导Tenured Associate Professor (英才副教授,特聘研究员) School of New Media and Communication Contact: shaoml@tju.edu.cn |
We are looking for highly motivated Ph.D., master, and undergraduate students to join our group. If you are interested in the position, please send your application to Prof. Shao.
Research Interests
- Deep Learning, Machine Learning, Trustworthy AI.
- Anomaly Detection, Graph Mining.
- Intelligent Communication, Natural Language Processing.
- Data Mining and Data Science in Real-world Applications.
Eduction Experience
Minglai Shao received his doctoral degree in the School of Computer Science and Engineering from Beihang University, under the supervision of Prof. Jianxin Li. He was a visiting scholar at the State University of New York.
Academic Activities
- PC:WWW, IJCAI, KDD, AAAI, WSDM, ECAI, etc.
- Reviewer: WWW, IJCAI, TDSC, TIFS, TKDE, ICDM, WSDM, KDD, AAAI, TNNLS, NIPS, etc.
Publications
2024
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Graph Collaborative Expert Finding with Contrastive Learning
Q.Peng, H. Liu, C. Huo, Minglai Shao*, W. Wang
The 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024) (CCF A) -
Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments
Y. Lin, C. Zhao, Minglai Shao*, B. Meng, X. Zhao, H., Chen
The 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024) (CCF A) -
Supervised Algorithmic Fairness in Distribution Shifts: A Survey
Minglai Shao*, Li, C. Zhao, X. Wu, Y. Lin, Tian
The 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024) (CCF A) -
Graph Bayesian Optimization for Multiplex Influence Maximization
Z. Yuan, Minglai Shao*, Z. Chen
The Annual AAAI Conference on Artificial Intelligence (AAAI 2024) (CCF A) -
Graph Contrastive Learning via Interventional View Generation
Z., Minglai Shao*, et al
The ACM Web Conference 2024 (WWW 2024) (CCF A) -
Deep Expertise and Interest Personalized Transformer for Expert Finding
Y. Wang, Q.Peng, H. Liu, H. Xu, Minglai Shao*, W. Wang*
Information Processing & Management (IPM) (SCI 1区) -
Learning Fair Invariant Representations under Covariate and Correlation Shifts Simultaneously.
D. Li, C. Zhao, Minglai Shao*, W. Wang*.
In Proceedings of the ACM International Conference on Information and Knowledge Management(CIKM), 2024 (CCF B) -
Dynamic heterogeneous graph contrastive networks for knowledge tracing.
Y. Han, H. Tang, W. Zhang, L. Du, J. Zhao, Minglai Shao
Applied Soft Computing, 2024 (SCI 1区) -
Addressing Graph Anomaly Detection via Causal Edge Separation and Spectrum
Z. Wo, W. Wang, Minglai Shao*, C. Liu, Y. Wang, Y. Sun
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
Out-of-Distribution Detection for Heterogeneous Graph Neural Networks
T. Yin, C. Zhao, Minglai Shao*
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
HyperDG: A Hypergraph-Based Approach for Dynamic Graph Node Classification under Spatio-Temporal Shift
X. Ma, C. Zhao, Minglai Shao*
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
IDGG: Invariant Learning for Out-of-Distribution Generalization on Graphs
Q. Tian, W. Wang, Minglai Shao*,C. Zhao, D. Li
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
Semantic OOD Detection under Covariate Shift on Graphs with Diffusion Model
Z. He, C. Zhao, Minglai Shao*, Y. Lin, D. Li
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
Fair Data Generation via Score-based Diffusion Model
Y. Lin, D. Li, C. Zhao, Minglai Shao*
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
Improving Fairness in Graph Neural Networks via Counterfactual Debiasing
Z. Wo, C. Liu, C. Zhao, Y. Wang, Minglai Shao*, W. Wang
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
CeDFormer: Community Enhanced Transformer for Dynamic Network Embedding
J. Guo, T. Li, Minglai Shao, W. Wang, et al
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops. (CCF A-W) -
LLM: Harnessing Large Language Models for Personalized Review Generation
Q Peng, H Liu, H Xu, Q Yang, M Shao, W Wang
arXiv preprint arXiv:2407.07487 -
Diffusion Review-based Recommendation
X. He, Q.Peng, Minglai Shao, Y. Sun
The 17th International Conference on Knowledge Science, Engineering and Management -
[Orgnizer, Chair] Workshops on Robust Machine Learning for Distribution Shifts (RobustMLDS)
1st workshop at IEEE Bigdata'24 -
[Orgnizer, Chair] 2024 IEEE Big Data Cup: Challenges of Trustworthy AI in Distribution Shifts and Algorithmic Fairness
1st BigData Cup Challenges at IEEE Bigdata'24
2023
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Motif-level Anomaly Detection in Dynamic Graphs[J]
Z. Yuan, Minglai Shao* , Q. Yan
IEEE Transactions on Information Forensics and Security (TIFS), 2023. (CCF A, SCI 1区) -
Multi-view Change Point Detection in Dynamic Networks[J]
Y. Xie, W. Wang, Minglai Shao* , T. Li, Y. Yu
Information Sciences, 2023. (CCF B, SCI 1区) -
Heterogeneous Network Representation Learning Based on Role Feature Extraction
Y. Sun, M. Jia, C, Liu, Minglai Shao*
Pattern Recognition, 2023. (CCF B, SCI 1区) -
Contrastive Representation Learning Based on Multiple Node-centered Subgraphs.
D. Li, W. Wang, Minglai Shao* , C. Zhao.
In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper, oral), 2023 (CCF B) -
Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs.
J. Li, Y. Sun, Minglai Shao* .
In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper, oral), 2023 (CCF B) -
Adaptation Speed Analysis for Fairness-aware Causal Models.
Y. Lin, C. Zhao, Minglai Shao* , X. Zhao and H. Chen.
In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper, oral), 2023 (CCF B) -
Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot Filling.
Y. Shi, Wu, Minglai Shao*
The 2023 Conference on Empirical Methods in Natural Language Processing(EMNLP), (CCF B) -
Learning Graph Deep Autoencoder for Anomaly Detection in Multi-attributed Networks.
Minglai Shao, Y. Lin, Q. Peng, W., Y. Sun
Knowledge-Based Systems, 2023. (SCI 1区) -
RHGNN: Fake Reviewer Detection Based on Reinforced Heterogeneous Graph Neural Networks
J. Zhao, Minglai Shao, H. Tang, J. Liu, L. Du, H, Wang.
Knowledge-Based Systems, 2023. (SCI 1区) -
Robust Few-shot Graph Anomaly Detection via Graph Coarsening.
L. Li, Y. Sun, T. Li, and Minglai Shao* .
The 16th International Conference on Knowledge Science, Engineering and Management, 2023. -
Joint Community and Structural Hole Spanner Detection via Graph Contrastive Learning.
J. Zhang, W. Wang, T. Li , Minglai Shao* , et al.
The 16th International Conference on Knowledge Science, Engineering and Management, 2023. -
Learning Fair and Domain Generalization Representation.
C. Zhao, Minglai Shao* , X. Zhao,
The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshop on Ethical Artificial Intelligence: Methods and Applications (KDD-EAI), 2023. (CCF A-W) -
Adaptation Speed of Causal Models Concerning Fairness.
Y. Lin, C. Zhao, Minglai Shao* , X. Zhao, H. Chen.
The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshop on Ethical Artificial Intelligence: Methods and Applications (KDD-EAI), 2023. (CCF A-W) - Achieving Counterfactual Fairness in Changing Environments via Sequential Autoencoder.
Y. Lin, C. Zhao, Minglai Shao* , X. Zhao, B. Meng, H. Chen
NeurIPS Workshop on Algorithmic Fairness through the Lens of Time (AFT), 2023 (CCF A-W) -
Detecting Multi-Label Out-of-Distribution Nodes on Graphs
X. Zhao, C. Zhao, Minglai Shao*
Thirty-Seventh AAAI Conference on Artificial Intelligence Workshops 2023. (CCF A-W) -
Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains
Y. Lin, C. Zhao, Minglai Shao*, B. Meng, X. Zhao, H. Chen.
arXiv preprint arXiv:2309.13005, 2023. -
Deep Cross-Network Alignment with Anchor Node Pair Diverse Local Structure[J].
Y. Wang, W. Wang, Minglai Shao, et al.
Algorithms, 2023, 16(5): 234.
Prior to 2023
-
Towards a Multi-view Attentive Matching for Personalized Expert Finding [C].
Qiyao Peng, Hongtao Liu, Yinghui Wang, Hongyan Xu, Pengfei Jiao, Minglai Shao*, Wenjun Wang.
Proceedings of the ACM Web Conference (WWW), 2022 (CCF-A) -
IISD: Integrated interaction subgraph detection for event mining[J]
Y. Yu, W. Wang, N. Wu, Liu H., Minglai Shao*
Knowledge-Based Systems, 2022. (SCI 1区) -
Cyber threat prediction using dynamic heterogeneous graph learning[J]
Jun Zhao, Minglai Shao, Hong Wang, Xiaomei Yu, Bo Li, Xudong Liu
Knowledge-Based Systems, 2022 (SCI 1区) -
Towards Comprehensive Expert Finding with a Hierarchical Matching Network
Qiyao Peng, Wenjun Wang, Hongtao Liu, Minglai Shao*
Knowledge-Based Systems, 2022 (SCI 1区) -
Combining Heterogeneity of Anchor Nodes for Network Alignment[J]
Yinghui Wang, Qiyao Peng, Wenjun Wang, Xuan Guo, Minglai Shao*, Hongtao Liu, Wei Liang, Lin Pan.
Knowledge-Based Systems, 2022. (SCI 1区) -
Multi-users Interaction Anomalous Subgraph Detection for Event Mining.
Yang Yu, Wenjun Wang, Minglai Shao, Nannan Wu, Ying Sun, Yueheng Sun, Qiang Tian.
Neurocomputing, 2022. -
Dual Perspective Contrastive Learning Based Subgraph Anomaly Detection on Attributed Networks
Sunlin Hu, Minglai Shao*
31st International Conference on Artificial Neural Networks, 2022. -
Role-Oriented Dynamic Network Embedding.
Ting Pan, Wenjun Wang, Minglai Shao*, Yueheng Sun, and Pengfei Jiao.
2022 IEEE International Conference on Big Data. -
Expertise-oriented Explainable Question Routing
Yulu Li, Qiyao Peng, Hongtao Liu, Minglai Shao* , Pengfei Jiao, and Wenjun Wang.
EAI CollaborateCom 2022. -
Geometry Interaction Network Alignment.
Yinghui Wang, Wenjun Wang, Zixu Zhen, Qiyao Peng, Pengfei Jiao, Wei Liang, Minglai Shao, Yueheng Sun.
Neurocomputing, 2022.
-
Structured sparsity model based trajectory tracking using private location data release[J]
Minglai Shao, Jianxin Li, Qiben Yan, Feng Chen, Hongyi Huang, Xunxun Chen
IEEE Transactions on Dependable and Secure Computing (TDSC), 2021 (CCF A, SCI 1区) -
MASA: An efficient framework for anomaly detection in multi-attributed networks[J]
Minglai Shao, Jianxin Li, Yue Chang, Jun Zhao, Xunxun Chen.
Computers & Security, 2021. (CCF B) -
A novel combined dynamic ensemble selection model for imbalanced data to detect COVID-19 from complete blood count[J].
Jiachao Wu, Jiang Shen, Man Xu, Minglai Shao*.
Computer Methods and Programs in Biomedicine, 2021. (SCI Q1) -
PGraph: A Graph-based Structure for Interactive Event Exploration on Social Media[C]
Yang Yu, Minglai Shao*, Hongyan Xu, Ying Sun, Wenjun Wang, Bofei Ma.
2021 2th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2021: 72-1. -
Porn2Vec: A robust framework for detecting pornographic websites based on contrastive learning[J].
Jun Zhao, Minglai Shao, Hao Peng, Hong Wang, Bo Li, Xudong Liu.
Knowledge-Based Systems, 2021.(SCI 1区) -
Automatically predicting cyber attack preference with attributed heterogeneous attention networks and transductive learning[J]
Jun Zhao, Xudong Liu, Qiben Yan, Bo Li, Minglai Shao, Hao Peng, Lichao Sun.
Computers & Security, 2021.(CCF B)
-
Multi-attributed heterogeneous graph convolutional network for bot detection[J].
Jun Zhao, Xudong Liu, Qiben Yan, Bo Li, Minglai Shao, Hao Peng.
Information Sciences, 2020. (CCF B, SCI 1区) -
Tree decomposition based anomalous connected subgraph scanning for detecting and forecasting events in attributed social media networks[J].
Minglai Shao, Peiyuan Sun, Jianxin Li, Qiben Yan, Zhirui Feng.
Neurocomputing, 2020. -
TIMiner: Automatically extracting and analyzing categorized cyber threat intelligence from social data[J].
Jun Zhao, Qiben Yan, Jianxin Li, Minglai Shao, Zuti He, Bo Li.
Computers & Security, 2020, 95: 10167. (CCF B) -
An efficient framework for detecting evolving anomalous subgraphs in dynamic networks[C]
Minglai Shao, Jianxin Li, Feng Chen, Xunxun Chen.
IEEE INFOCOM 201-IEEE Conference on Computer Communications (INFOCOM), 201 (CCF A) -
An efficient approach to event detection and forecasting in dynamic multivariate social media networks[C]
Minglai Shao, Jianxin Li, Feng Chen, Hongyi Huang, Shuai Zhang, Xunxun Chen.
Proceedings of the 26th International Conference on World Wide Web(WWW), 2017 (CCF A) -
Stacked kernel network[J].
Shuai Zhang, Jianxin Li, Pengtao Xie, Yingchun Zhang, Minglai Shao, Haoyi Zhou, Mengyi Yan.
arXiv preprint arXiv:1711.09219, 2017. -
Clustering Algorithm Combined Granular Computing, Ant Colony Algorithm and Fuzzy Idea.
Minglai Shao, Liangxi Qin.
Computer Technology and Development. 2015. -
Text similarity computing based on LDA topic model and word co-occurrence[C]
Minglai Shao, Liangxi Qin.
Proceedings of the 2nd International Conference on Software Engineering, Knowledge Engineering and Information Engineering (SEKEIE 2014)
Awards/Honors
- The First Prize of the Second New Engineering Curriculum Design Competition of Tianjin University.
- “Best Researcher Award”
- Outstanding Graduate of Beijing.
- PhD National Scholarship.
- Zhonghangji Scholarship.
- CNCERT Outstanding Research Award.
- Top-10 Doctoral Students Candidate of Beihang University, etc.