| CARVIEW |
Select Language
HTTP/2 200
server: GitHub.com
content-type: text/html; charset=utf-8
last-modified: Mon, 08 Dec 2025 16:53:56 GMT
access-control-allow-origin: *
etag: W/"693702a4-12200"
expires: Tue, 30 Dec 2025 17:33:28 GMT
cache-control: max-age=600
content-encoding: gzip
x-proxy-cache: MISS
x-github-request-id: 7B2A:1387E:A459C7:B8AA3C:69540A8F
accept-ranges: bytes
age: 0
date: Tue, 30 Dec 2025 17:23:28 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210056-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1767115408.192930,VS0,VE208
vary: Accept-Encoding
x-fastly-request-id: e827fc9178f05b53b4a2f9a1d0f93094b5838762
content-length: 13758
Gauthier Gidel
Link to my Google scholar.
Fall 2021 - Fall 2022: Data Science -- IFT 6758-A -- Science des Données.
I identify to the fields of ML (JMLR, NeurIPS, ICML, AISTATS, COLT, and ICLR) and optimization (SIAM OP)
Quentin Bertrand, Tenured Research scientist at Inria Lyon
Joey Bose, Tenure Track Assistant Professor at Imperial college
Eduard Gorbunov, Tenure-Track Assistant Professor of Statistics and Data Science at MBZUAI
Bora Yongacoglu, Research Scientist at Yelp
Matthew Hough, Ph.D., University of Waterloo
Bilun Sun, AI Research Engineer
Chiara Régniez, Research Scientist, Owkin
Leonardo Cunha, Software Engineer, Muvraline
Sunand Raghupathi, Co-Founder - Veda
Aleksandr Beznosikov Ph.D. at MIPT.
Michael Przystupa Ph.D. at University of Alberta.
Alexandre Duplessis M.Sc. at Oxford.
Chris Junchi Li researcher at Private Sector Company in Shanghai, China (previous visiting postdoc co-supervised with Michael I. Jordan)
With my currents responsabilitities, I have no time to update this website frequently. Thus,
Gauthier Gidel is a Canada CIFAR AI Chair, a core member of Mila, and an assistant professor at the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. His research focuses on generative modeling and multi-objective learning, such as alignment or adversarial robustness. He is well known for his work on variational inequality for machine learning. Gauthier co-organized a popular series of workshops on smooth games during NeurIPS. He also co-founded and co-organized the first three iterations of the ICLR blog post track.
Gauthier Gidel
Pavillon André-Aisenstadt
2920 Chemin de la Tour, office 3151
Montreal, QC
H3T 1J4 CANADA
Gauthier Gidel
Assistant Professor
Université de Montréal - DIRO
Core member of Mila
I am an Associate Professor at Université de Montréal in the DIRO (Department of Computer Science and Operational Research), a core member of Mila, and a Canada CIFAR AI Chair holder (Phase I and II). I am also one of the co-leaders of the IVADO research cluster on Machine Learning. I completed my PhD at Université de Montréal under the supervision of Simon Lacoste-Julien, where I was awarded a Borealis AI fellowship and two DIRO Excellence Grants. During my Ph.D., I have been an intern at Sierra, ElementAI and DeepMind.
Prospective Students
Please read this page before sending me any email.
Courses
Fall 2021 - Fall 2022: Data Science -- IFT 6758-A -- Science des Données.
- I am teaching the data science class in french this fall.
My Research
- Adversarial Robustness of LLMs' Safety Alignment: How can we build safer LLMs and improve the evaluation of their robustness?
- Cooperation and Negotiation in Multi-Agent Contexts: How can we design algorithms that can learn the long-term benefit of cooperation while still maintaining a high value for their objective? In a world where rational agents first serve their interests, negotiation protocols and robustness are essential to reaching a high level of cooperation.
- Principled Learning Method for (Multi-Agent) RL: Can we design training methods that tackle the challenges of learning in non-stationary environments?
- Risk and Benefit of Interaction with Synthetic Data: When and to what extent can synthetic data improve (or deteriorate) the performance of models trained on these data? How do generative models affect each other's learning when deployed in shared environments?
I identify to the fields of ML (JMLR, NeurIPS, ICML, AISTATS, COLT, and ICLR) and optimization (SIAM OP)
Members of my Lab (by alphabetical order)
- David Dobre (Ph.D.)
- Damien Ferbach, (Ph.D., co-supervised with Courtney Paquette)
- Marco Jiralerspong (Ph.D.)
- Zichu Liu, (Ph.D. co-supervized with Ioannis Mitliagkas)
- Andjela Mladenovic (Ph.D., co-supervised with Aaron Courville)
- Mehrnaz Mofakhami (Research Assistant)
- Motahareh Sohrabi (Research Assistant co-supervized with Simon Lacoste Julien)
- Tom Stanic (Intern)
- Danilo Vucetic, (Ph.D.)
- Sophie Xhonneux (Ph.D., co-supervised with Jian Tang)
Alumni
Preprints - Publications - Manuscripts
With my currents responsabilitities, I have no time to update this website frequently. Thus, this List is not up-to-date, I decided to remove the list on my website, for my latest publications please check my Google Scholar
Third Person Bio
Gauthier Gidel is a Canada CIFAR AI Chair, a core member of Mila, and an assistant professor at the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. His research focuses on generative modeling and multi-objective learning, such as alignment or adversarial robustness. He is well known for his work on variational inequality for machine learning. Gauthier co-organized a popular series of workshops on smooth games during NeurIPS. He also co-founded and co-organized the first three iterations of the ICLR blog post track.
Contact
Gauthier Gidel
Pavillon André-Aisenstadt
2920 Chemin de la Tour, office 3151
Montreal, QC
H3T 1J4 CANADA