Hi! I’m a Ph.D. student at Mila and Université de Montréal, advised by Irina Rish and Eugene Belilovsky. I’m currently researching efficient foundation model pre-training through two lenses: continual learning and meta-learning.

I received my MMath in Computer Science from the University of Waterloo, where I was was a member of the WISE Lab advised by Krzysztof Czarnecki. My research focused on developing 3D computer vision algorithms for object re-identifiation from point clouds.

I received by BSc in Computer Science from Concordia Univsersity, where I completed software engineering internships at Accedian and Morgan Stanley. I also completed research internships in the CLaC Lab advised by Sabine Bergler and at Mila advised by Eugene Belilovsky and Guy Wolf.

Research Publications

[9] Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky. μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. In Submission to NeurIPS 2024.

[8] Adam Ibrahim*, Benjamin Thérien*, Kshitij Gupta*, Mats Leon Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, and Irina Rish. Simple and Scalable Strategies to Continually Pre-train Large Language Models Published in Transactions on Machine Learning Research (06/2024)

[7] Charles-Étienne Joseph*, Benjamin Thérien*, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky. Learning Optimizers for Local SGD. In International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023.

[6] Kshitij Gupta*, Benjamin Thérien*, Adam Ibrahim*, Mats Leon Richter, Quentin Anthony, Eugene Belilovsky, Timothée Lesort, and Irina Rish. Continual Pre-Training of Large Language Models: How to re-warm your model? In Efficient Systems for Foundation Models Workshop at ICML 2023, Honolulu, USA.

[5] Benjamin Thérien, Chengjie Huang, Adrian Chow, Krzysztof Czarnecki. Object Re-Identification from Point Clouds. In proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.

[4] Luke Rowe*, Benjamin Thérien*, Krzysztof Czarnecki, and Hongyang Zhang. An Exploration of Robustness to L-infinity and Spatial Perturbations and their Composition. (ArXiv)

[3] Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Mannes, Luke Rowe, Benjamin Thérien, Rick Salay, Krzysztof Czarnecki. Out-of-Distribution Detection for LiDAR-based 3D Object Detection. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC).

[2] (Oral: 4.2% of submissions) Shanel Gauthier*, Benjamin Thérien*†, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf. Parametric Scattering Networks. In proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

[1] Benjamin Therien, Parsa Bagherzadeh, and Sabine Bergler. CLaC-BP at SemEval-2021 Task 8 : SciBERT Plus Rules for MeasEval. In Proceedings of the Fifteenth Workshop on Semantic Evaluation (SemEval-2021). Association for Computational Linguistics.

--- †: Oral presenter. *: Equal contribution.