Assistant Professor, School of Computing
| wei.13.zhang@uconn.edu | |
| Mailing Address | University of Connecticut 371 Fairfield Way, Unit 4155 Storrs, CT 06269-4155 |
| Campus | Storrs |
Brief Bio
Dr. Zhang is an Associate Professor of Computer Science and Engineering at the University of Connecticut since 2024. His research interests center around machine learning and data science. Recently, he has focused on developing foundational, resource-efficient, and safe machine learning algorithms and models, particularly on graph and text data. Besides, he applies them to applications in various domains including public health/healthcare, social media, recommender systems, and natural language processing. His works are majorly published in top conferences of AI, machine learning, and data science. Dr. Zhang directs the Machine Intelligence and Data Science (MINDS) Lab.
He has received some awards and honors such as IJCAI Early Career Spotlight (2025), ICBS Frontiers of Science Award (2024), and NSF CAREER Award (2024). His work won several Best Paper Awards or nominations in leading conferences.
Before joining UConn, he was an Assistant Professor of Computer Science at the Brandeis University (2020-2024). He completed his PhD in Computer Science and Engineering at the University of Notre Dame (2017-2020), advised by Professor Nitesh Chawla.
- Machine Learning,
- Data Mining,
- Graph Machine Learning,
- Large Language Models,
- Resource-Efficient Machine Learning,
- AI for Society,
- AI Safety
- Big Data Analytics (Fall 2025)
- Deep Learning (Spring 2021, Spring 2022, Spring 2023, Fall 2024)
- Graph Machine Learning (Fall 2020, Fall 2021, Fall 2022)
- Artificial Intelligence (Fall 2023)
| Heterogeneous graph neural network
C Zhang, D Song, C Huang, A Swami, NV Chawla
Proceedings of the 25th ACM SIGKDD international conference on knowledge …
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| A deep neural network for unsupervised anomaly detection and diagnosis in multivariate time series data
C Zhang, D Song, Y Chen, X Feng, C Lumezanu, W Cheng, J Ni, B Zong, ...
Proceedings of the AAAI Conference on Artificial Intelligence 33, 1409-1416
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| Dynamics of information diffusion and its applications on complex networks
ZK Zhang, C Liu, XX Zhan, X Lu, CX Zhang, YC Zhang
Physics Reports 651, 1-34
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| Collaborative User Network Embedding for Social Recommender Systems
C Zhang, L Yu, Y Wang, C Shah, X Zhang
Proceedings of the 2017 SIAM International Conference on Data Mining, 381-389
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| Few-shot knowledge graph completion
C Zhang, H Yao, C Huang, M Jiang, Z Li, NV Chawla
Proceedings of the AAAI conference on artificial intelligence 34 (03), 3041-3048
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| Few-shot graph learning for molecular property prediction
Z Guo, C Zhang, W Yu, J Herr, O Wiest, M Jiang, NV Chawla
Proceedings of the web conference 2021, 2559-2567
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| Graph few-shot learning via knowledge transfer
H Yao, C Zhang, Y Wei, M Jiang, S Wang, J Huang, N Chawla, Z Li
Proceedings of the AAAI conference on artificial intelligence 34 (04), 6656-6663
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| Multi-modal self-supervised learning for recommendation
W Wei, C Huang, L Xia, C Zhang
Proceedings of the ACM web conference 2023, 790-800
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| Self-supervised hypergraph transformer for recommender systems
L Xia, C Huang, C Zhang
Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …
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| Shne: Representation learning for semantic-associated heterogeneous networks
C Zhang, A Swami, NV Chawla
Proceedings of the twelfth ACM international conference on web search and …
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| Heterogeneous graph masked autoencoders
Y Tian, K Dong, C Zhang, C Zhang, NV Chawla
Proceedings of the AAAI conference on artificial intelligence 37 (8), 9997-10005
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| Multi-order attentive ranking model for sequential recommendation
L Yu, C Zhang, S Liang, X Zhang
Proceedings of the AAAI conference on artificial intelligence 33 (01), 5709-5716
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| Mist: A multiview and multimodal spatial-temporal learning framework for citywide abnormal event forecasting
C Huang, C Zhang, J Zhao, X Wu, D Yin, N Chawla
The world wide web conference, 717-728
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| Online purchase prediction via multi-scale modeling of behavior dynamics
C Huang, X Wu, X Zhang, C Zhang, J Zhao, D Yin, NV Chawla
Proceedings of the 25th ACM SIGKDD international conference on knowledge …
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| Graph-based molecular representation learning
Z Guo, K Guo, B Nan, Y Tian, RG Iyer, Y Ma, O Wiest, X Zhang, W Wang, ...
arXiv preprint arXiv:2207.04869
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| Epidemic spreading on weighted complex networks
Y Sun, C Liu, CX Zhang, ZK Zhang
Physics Letters A 378 (7-8), 635-640
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| Learning mlps on graphs: A unified view of effectiveness, robustness, and efficiency
Y Tian, C Zhang, Z Guo, X Zhang, N Chawla
The Eleventh International Conference on Learning Representations
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| Heterogeneous temporal graph neural network
Y Fan, M Ju, C Zhang, Y Ye
Proceedings of the 2022 SIAM international conference on data mining (SDM …
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| Hierarchically structured transformer networks for fine-grained spatial event forecasting
X Wu, C Huang, C Zhang, NV Chawla
Proceedings of the web conference 2020, 2320-2330
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| Camel: Content-aware and meta-path augmented metric learning for author identification
C Zhang, C Huang, L Yu, X Zhang, NV Chawla
Proceedings of the 2018 World Wide Web Conference, 709-718
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