Jian Tang
About
Appointed Canada CIFAR AI Chair – 2019
Renewed Canada CIFAR AI Chair – 2025
Jian Tang is a Canada CIFAR AI Chair at Mila and an assistant professor at HEC Montréal and an associate professor at Université de Montréal. He worked as a research associate at Microsoft Research Asia between 2014-2016.
Tang’s research interests include geometric deep learning, deep generative models, and their applications in protein and small molecule design. He is also the founder of the startup BioGeometry, focusing on generative AI for protein design.
Awards
- AI 2000 Most Influential Scholar, 2020, 2022, 2023
- Applied Research Accelerator Award, NVIDIA, 2022
- Faculty Research Award, Amazon, 2020
- Best paper nomination, World Wide Web Conference, 2016
- Most-Cited Paper, World Wide Web Conference, 2015
- Best Paper Award, ICML, 2014
Relevant Publications
- Zhang, Z., Xu, M., Jamasb, A., Chenthamarakshan, V., Lozano, A., Das, P., & Tang, J. (2023). Protein representation learning by geometric structure pretraining. ICLR.
- Hua, C., Rabusseau, G., & Tang, J., (2022). High-Order Pooling for Graph Neural Networks with Tensor Decomposition. Thirty-sixth Conference on Neural Information Processing Systems.
- Wang, X., Gao, T., Zhu, Z., Zhang, Z., Liu, Z., Li, J., & Tang, J. (2021). KEPLER: A unified model for knowledge embedding and pre-trained language representation. Transactions of the Association for Computational Linguistics, 9, 176-194.
Sun, Z., Deng, Z. H., Nie, J. Y., & Tang, J. (2019). Rotate: Knowledge graph embedding by relational rotation in complex space.
Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., & Mei, Q. (2015). Line: Large-scale information network embedding. In Proceedings of the 24th international conference on world wide web (pp. 1067-1077).