Muhan is currently a PhD student in computer science at Washington University in St. Louis. His advisor is Prof. Yixin Chen. Before WashU, he obtained a bachelor degree from Shanghai Jiao Tong University as a member of the IEEE honor class, where he worked with Prof. Ya Zhang. He did an internship at Facebook as a research scientist in the summer of 2018, working with Anand Bhaskar.
Machine Learning, Data Mining, with particular interests in deep learning and learning with graphs, e.g., link prediction in social networks, graph neural networks etc.
- M. Zhang, S. Jiang, Z. Cui, R. Garnett, and Y. Chen, D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, arXiv:1904.11088, 2019. (Preprint)(Source code)
- M. Zhang and Y. Chen, Inductive Graph Pattern Learning for Recommender Systems Based on a Graph Neural Network, arXiv:1904.12058, 2019. (Preprint)(Source code)
- Z. Cui, M. Zhang, and Y. Chen, Deep Embedding Logistic Regression, Proc. IEEE International Conference on Big Knowledge (ICBK-18), 2018. (PDF)
- M. Zhang and Y. Chen, Link Prediction Based on Graph Neural Networks, Advances in Neural Information Processing Systems (NeurIPS-18), spotlight presentation, 2018. (Only 168 out of 4856 submissions are accepted as spotlight presentations) (PDF)(Source code)(Website)
- M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, Proc. AAAI Conference on Artificial Intelligence (AAAI-18), 2018. (PDF)(Supplement)(Source code)
- M. Zhang, Z. Cui, S. Jiang, and Y. Chen, Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space, Proc. AAAI Conference on Artificial Intelligence (AAAI-18), 2018. (PDF)(Source code)
- M. Zhang and Y. Chen, Weisfeiler-Lehman Neural Machine for Link Prediction, Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-17), oral presentation, 2017. (Only 64 out of 748 submissions are accepted as oral presentations) (PDF)(Video)(Slides)(Source code)
- (*Equal-contribution primary author) T. Oyetunde*, M. Zhang*, Y. Chen, Y. Tang, and C. Lo, BoostGAPFILL: Improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods, Bioinformatics, 33(4):608-611, 2017. (PDF)
- L. He, S. Wu, M. Zhang, Y. Chen, and Y. Tang, WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism, BMC Bioinformatics, 17.1 (2016): 444. (PDF)
- W. Cai, M. Zhang, and Y. Zhang, Batch Mode Active Learning for Regression With Expected Model Change, IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , (2016): 1-14. (PDF)
- W. Cai, M. Zhang, and Y. Zhang, Active learning for ranking with sample density, Information Retrieval Journal , 18.2 (2015): 123-144. (PDF)
- W. Cai, M. Zhang, and Y. Zhang, Active learning for Web search ranking via noise injection, ACM Transactions on the Web (TWEB), 9.1 (2015): 3. (PDF)