Reihaneh Rabbany
About
Appointed Canada CIFAR AI Chair – 2018
Renewed Canada CIFAR AI Chair – 2023
Reihaneh Rabbany is a Canada CIFAR AI Chair and an assistant professor at the School of Computer Science at McGill University. Before that she was a postdoctoral fellow at the School of Computer Science, Carnegie Mellon.
Rabbany’s research is at the intersection of network science, data mining and machine learning, with a focus on developing techniques for analyzing large-scale complex data that is interconnected, evolving, multi-modal, and noisy. She is particularly interested in data from online societies and applications to enhance the health and safety of online spaces.
Relevant Publications
- Nair, P., Liu, J., Vajiac, C., Olligschlaeger, A., Chau, D. H., Cazzolato, M., Jones, C., Faloutsos, C. & Rabbany, R. (2024). T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking. In Proceedings of the AAAI Conference on Artificial Intelligence.
- Huang, S., Poursafaei, F., Danovitch, J., Fey, M., Hu, W., Rossi, E., Leskovec, J., Bronstein, M.M., Rabusseau, G., & Rabbany, R. (2023). Temporal Graph Benchmark for Machine Learning on Temporal Graphs. Proceedings of the 37th Conference on Neural Information Processing Systems.
- Poursafaei, F., Huang, S., Pelrine, K., & Rabbany, R. (2022). Towards Better Evaluation for Dynamic Link Prediction. In Proceedings of the 36th Conference on Neural Information Processing Systems.
- Pelrine, K., Danovitch, J., & Rabbany, R. (2021). The Surprising Performance of Simple Baselines for misinformation Detection. In Proceedings of the 30th Web Conference.
- Huang, S., Hitti, Y., Rabusseau, G., & Rabbany, R. (2020). Laplacian Change Point Detection for Dynamic Graphs. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.