Farimah Poursafaei

Joined

June 2022

Names

Farimah Poursafaei (Preferred)

Emails

****@mila.quebec (Confirmed)

****@gmail.com (Confirmed)

****@mail.mcgill.ca (Confirmed)

Personal Links

Google Scholar

DBLP

Career & Education History

Postdoc

School of Computer Science , McGill University (mcgill.ca)

2022 – 2025

Intern

Valence Labs powered by recursion (valencelabs.com)

2023 – 2024

Postdoc

Mila, Quebec AI Institute (mila.quebec)

2022 – 2024

PhD student

McGill University (mcgill.ca)

2017 – 2022

Advisors, Relations & Conflicts

Coworker

Shenyang Huang

2022 – 2025

PhD Advisor

Reihaneh Rabbany

2019 – 2025

Coauthor

Dominique Beaini

2023 – 2024

Postdoc Advisor

Reihaneh Rabbany

2022 – 2024

Expertise

No areas of expertise listed

Publications

Hydra: Towards Transferable Multi-Task Learning on Temporal Graphs
Kiarash Shamsi, Farimah Poursafaei, Tran Gia Bao Ngo, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Shenyang Huang, Cuneyt Gurcan Akcora
- Submitted to ICLR 2026
- Readers: Everyone
TGM: A Modular and Efficient Library for Machine Learning on Temporal Graphs
Jacob Chmura, Shenyang Huang, Tran Gia Bao Ngo, Ali Parviz, Farimah Poursafaei, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Matthias Fey, Reihaneh Rabbany
- ICLR 2026 Poster
- Readers: Everyone
Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning
Zifeng Ding, Shenyang Huang, Zeyu Cao, Emma Kondrup, Zachary Yang, Xingyue Huang, Yuan Sui, Moy Yuan, Yuqicheng Zhu, Xianglong Hu, Yuan He, Farimah Poursafaei, Michael M. Bronstein, Andreas Vlachos
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning
Zifeng Ding, Shenyang Huang, Zeyu Cao, Emma Kondrup, Zachary Yang, Xingyue Huang, Yuan Sui, Moy Yuan, Yuqicheng Zhu, Xianglong Hu, Yuan He, Farimah Poursafaei, Michael M. Bronstein, Andreas Vlachos
- NPGML Poster
- Readers: Everyone
TGM: A Modular Framework for Machine Learning on Temporal Graphs
Jacob Chmura, Shenyang Huang, Ali Parviz, Farimah Poursafaei, Michael M. Bronstein, Guillaume Rabusseau, Matthias Fey, Reihaneh Rabbany
- CODEML@ICML25
- Readers: Everyone
MiNT: Multi-Network Transfer Benchmark for Temporal Graph Learning
Kiarash Shamsi, Tran Gia Bao Ngo, Razieh Shirzadkhani, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Cuneyt Gurcan Akcora
- NeurIPS 2025 Datasets and Benchmarks Track poster
- Readers: Everyone
Towards Neural Scaling Laws for Foundation Models on Temporal Graphs
Razieh Shirzadkhani, Tran Gia Bao Ngo, Kiarash Shamsi, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Guillaume Rabusseau, Cuneyt Gurcan Akcora
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Temporal Graph Rewiring with Expander Graphs
Katarina Petrović, Shenyang Huang, Farimah Poursafaei, Petar Veličković
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs
Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi
- LoG 2024 Poster
- Readers: Everyone
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
Julia Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau
- OpenReview Archive Direct Upload
- Readers: Everyone

View all 38 publications

Co-Authors

View all 54 co-authors