Reihaneh Rabbany
Canada CIFAR AI Chair, MilaAssistant Professor
School of Computer Science
McGill University
Office: 232 McConnell, D16 Mila
Phone: (514)398[dash]3281
Email: rrabba[at]cs.mcgill.ca
My main research interest is complex data analysis. Complex data is often interconnected, evolving, and hard to label. With my group, at Complex Data Lab, we work on designing methods for analyzing such data; building on techniques for graph mining, graph representation learning, unsupervised and self-supervised learning, anomaly detection, learning with weak and/or uncertain labels, and active and human-in-the-loop learning. Our research projects often involve working with real-world data from online societies, where we design methods closely with domain experts within an interdisciplinary team.
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Teaching
- Applied Machine Learning
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- Syllabus for COMP 551 - Fall 2023
- archived versions: COMP 551 - Winter 2020, COMP 551 - Winter 2021, COMP 551 - Winter 2022, COMP 551 - Winter 2023
- Network Science
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- archived versions: COMP 596 - Fall 2019 , COMP 596 - Fall 2020, COMP 599 - Fall 2021, COMP 599 - Fall 2022
Group
- Complex data lab's Github & Twitter , If you are interested to join our lab, please read this.
- Current members
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- Farimah Poursafaei, Postdoc, 2022-
- Aarash Feizi, PhD student, co-supervised with Adriana Romero, 2019-
- Andy Huang, PhD student, co-supervised with Guillaume Rabusseau, 2019-
- Kellin Pelrine, PhD student, 2020-
- Pratheeksha Nair, PhD student, 2020-
- Zachary Yang, PhD student, 2021-
- Elahe Kooshafar, MSc student, 2022-
- Sahar Shayegan, MSc student, co-supervised with Isar Nejadgholi , 2022-
- Soroush Omranpour, MSc student, co-supervised with Guillaume Rabusseau, 2022-
- Vidya Sujaya, MSc student, 2023-
- Mark Ezema, Software developer, 2023-
- Sophia Garrel, Research associate in criminology, 2021-
- Anne Imouza, Research assistant in political science, 2022-
- Razieh Shirzadkhani, Research assistant, summer 2022-
- Javin Liu, Research assistant, summer 2022-
- Peter Yu, Research intern, summer 2023-
- Jacob Tian, Research intern, summer 2022-
- Cecile Amadoro, Research intern in political science, summer 2023-
- Andreea Musulan, Research affiliate in political science, summer 2023-
- Graduated members
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- Farimah Poursafaei, PhD student, co-supervised with Zeljko Zilic, 2020-2022
Thesis: Anomaly detection in cryptocurrency networks and beyond
Next position: Postdoc at Mila/McGill- Jacob Danovitch, MSc student, co-supervised with Fernando Diaz, 2020-2023
Thesis: Design Space Exploration of Graph Neural Networks for Inductive Link Prediction
Next position: Data and Applied Scientists at Microsoft- Maricarmen Arenas, MSc student at HEC Montreal, co-supervised with Golnoosh Farnadi, 2020-2023
Thesis: Social Media as a Vector for Escort Ads: A Study on OnlyFans advertisements on Twitter- Gabrielle Desrosiers-Brisebois, MSc student of Political Science at University of Montreal, co-supervised with Jean-François Godbout, 2020-2023
Thesis: Role of social bots in the 2021 Canadian federal election- Albert Orozco Camacho, MSc student, 2019-2023
Thesis: A Study of Social Media Trolls via Graph Representation Learning
Next position: PhD Student at Mila and University of Montreal- Anne Imouza, MSc student of Political Science at University of Montreal, co-supervised with André Blais, 2020-2022
Thesis: The impact of social bots on public COVID-19 perceptions during the 2020 U.S. presidential election
Next position: PhD student at McGill Political Science with Richard H. Tomlinson Doctoral Fellowship- Charlotte Ding, MSc student, 2019-2021
Thesis: Epidemiological modelling of a pandemic using mobility networks
Next position: Software Development Engineer at Expedia- Aayushi Kulshrestha, MSc student, 2018-2021
Thesis: Detection of organized activity in online escort advertisements
Next position: Software Engineer, Machine Learning role at Google- Junhao Wang, MSc student, 2018-2021
Thesis: Combating online misinformation by detecting organized groups on social media
Next position: Machine Learning Researcher at Microsoft Research- Liheng Ma, MSc student, co-supervised with Adriana Romero, 2018-2020
Thesis: Graph Attention Networks with auxiliary positional embedding models, winner of the Canadian Artificial Intelligence Association (CAIAC) 2021 Best Master's Thesis Award
Next position: PhD at McGill ECE- Sacha Levy, undergraduate research intern, 2019-2023
Next position: PhD at Yale CS- Yifei Li, undergraduate research intern, 2020-2021
Next position: Technology Associate at Morgan Stanley- Abby Leung, undergraduate research intern, summer 2020-2021,
Next position: PhD at the network science institute - Farimah Poursafaei, PhD student, co-supervised with Zeljko Zilic, 2020-2022
Publications
- Full list: google scholar, dblp
- Selected papers
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- Kellin Pelrine, Anne Imouza, Zachary Yang, Jacob Tian, Sacha Levy, Gabrielle Desrosiers-Brisebois, Aarash Feizi, Cecile Amadoro, Andre Blais, Jean-Francois Godbout , Reihaneh Rabbany, Party Prediction for Twitter, Proceedings of the 18th International Conference on Web and Social Media (AAAI ICWSM), 2024; arXiv version
- Andy Huang, Jacob Danovitch, Guillaume Rabusseau, Reihaneh Rabbany, Fast and Attributed Change Detection on Dynamic Graphs with Density of States, Proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023; arXiv version code on github
- Maricarmen Arenas, Pratheeksha Nair, Reihaneh Rabbany, Golnoosh Farnadi, Social Media as a Vector for Escort Ads: A Study on OnlyFans advertisements on Twitter, Proceedings of the 15th ACM Web Science Conference, 2023; publisher link
- Farimah Poursafaei, Shenyang Huang, Kellin Pelrine, Reihaneh Rabbany, Towards Better Evaluation for Dynamic Link Prediction, Proceedings of the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2022; publisher link code on github
- Kellin Pelrine, Jacob Danovitch, Reihaneh Rabbany, The Surprising Performance of Simple Baselines for Misinformation Detection, Proceedings of the 30th the Web Conference, April 2021; arXiv version code on github
- Liheng Ma, Reihaneh Rabbany, Adriana Romero, Graph Attention Networks with Positional Embeddings, Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021), May 2021;
- Meng-Chieh Lee, Catalina Vajiac, Aayushi Kulshrestha, Sacha Levy, Namyong Park, Cara Jones, Reihaneh Rabbany and Christos Faloutsos, InfoShield: Generalizable Information-Theoretic Human-Trafficking Detection, Proceedings of 37th IEEE International Conference on Data Engineering (ICDE), April 2021; code on github
- Andy Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany, Laplacian Change Point Detection for Dynamic Graphs, Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Aug 2020; video code on github
- Dhivya Eswaran, Reihaneh Rabbany, Artur W. Dubrawski, Christos Faloutsos, Social-Affiliation Networks: Patterns and the SOAR Model, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Sep 2018; code on github
- Reihaneh Rabbany, David Bayani, Artur W. Dubrawski, Active Search of Connections for Case Building and Combating Human Trafficking, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Aug 2018; video
- Reihaneh Rabbany, and Osmar R. Zaiane, A General Clustering Agreement Index: for Comparing Disjoint and Overlapping Clusters, Thirty-First AAAI Conference on Artificial Intelligence (AAAI), Feb 2017;
- Reihaneh Rabbany, and Osmar R. Zaiane, Generalization of clustering agreements and distances for overlapping clusters and network communities, Data Mining and Knowledge Discovery Journal (DAMI), 29(5): 1458-1485, 2015; code on github ECML PKDD Slides ; publisher link
Software
- Temporal Graph Benchmark (TGB), Benchmark datasets for machine learning on temporal graphs
- Community Evaluation, A framework available for evaluating community mining algorithms
- TopLeaders, Detecting the community/clustering structure in relational datasets
- MeerkatED, Mining the Network of Students in Online Courses using social network analysis techniques
Short bio
- Reihaneh Rabbany is an Assistant Professor at the School of Computer Science, McGill University. She is a core faculty member of Mila - Quebec's artificial intelligence institute, and a Canada CIFAR AI Chair. She is also a faculty member at the Center for the Study of Democratic Citizenship. Before joining McGill, she was a Postdoctoral fellow at the School of Computer Science, Carnegie Mellon University. She completed her Ph.D. in Computing Science Department at the University of Alberta. Her research is at the intersection of network science, data mining and machine learning, with a focus on analyzing real-world interconnected data, and social good applications.
high res photo , CV , google scholar,
dblp
