Reihaneh Rabbany

Reihaneh Rabbany is a Canada CIFAR AI Chair and Mila Assistant Professor at the School of Computer Science, McGill University. Her research focuses on network science, data mining, and applied machine learning, with an emphasis on analyzing complex, interconnected, and evolving data. She leads the Complex Data Lab, where her work involves graph mining, representation learning, and methods for handling weak or uncertain labels. Rabbany's research often addresses real-world data from online societies, collaborating with domain experts to design interdisciplinary solutions. She teaches courses in applied machine learning and network science and is affiliated with the Center for the Study of Democratic Citizenship.

Reihaneh Rabbany is an Associate Professor of Computer Science at McGill University and holds the Canada CIFAR AI Chair at Mila. Her research focuses on Data Mining, Machine Learning, Graph Mining, Network Science, and Computational Social Science. She explores methods for analyzing dynamic networks, evaluating link prediction, and detecting misinformation. Her work includes benchmarking temporal graphs, community detection in information networks, and social network analysis for educational settings. Rabbany also investigates the use of graph attention networks and blockchain transaction analysis for illicit activity detection. Her research emphasizes the development of robust models for understanding complex systems and improving misinformation mitigation.