| CARVIEW |
Hello! I am a Researcher at Mila working at Gauthier Gidel's lab. I recently completed my master's at Université de Montréal and Mila under the supervision of Gauthier Gidel and Ioannis Mitliagkas. During my studies, I spent some time at ServiceNow Research as a Visiting Researcher, where I worked with João Monteiro and Valentina Zantedeschi. Prior to coming to Montreal, I received my bachelor's degree at Sharif University of Technology in Computer Science.
I am interested in the fundamentals of machine learning, where I can explore how AI can be used effectively and efficiently to improve decision-making across various domains. My research has evolved from studying predictive models that actively shape the environments they're designed to analyze to improving inference optimization techniques that balance computational efficiency with performance. Currently, I'm working on uncovering hidden vulnerabilities in large language models and how to make them more robust.
If there's anything you'd like to discuss with me, feel free to email me at: mehrnaz (dot) mofakhami [at] mila.quebec or reach out on X!
News
Projects
Sophie Xhonneux*, David Dobre*, Mehrnaz Mofakhami*, Leo Schwinn, Gauthier Gidel
BuildingTrust Workshop, ICLR 2025 | * Equal Contribution
Paper
Mehrnaz Mofakhami, Reza Bayat, Ioannis Mitliagkas, João Monteiro*, Valentina Zantedeschi*
Efficient Systems for Foundation Models Workshop, ICML 2024 | * Equal Supervision
Paper
Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel
OPT for ML Workshop, NeurIPS 2024
Paper
António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Gauthier Gidel, Simon Lacoste-Julien
AISTATS 2025
Paper / Code
Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel
AISTATS 2023
Paper / Video
Mehrnaz Mofakhami, AmirHossein Yavari
EEML Summer School 2021 - Best poster award
Report / Code
Notes
Supplementary material for the Artificial Intelligence Course at SUT - Spring 2021
I wrote this short tutorial while I was a TA in the AI course at Sharif University of Technology. It is an introduction to the main topics in robust and trustworthy ML, including evasion and poisoning attacks, and mechanisms to defend against them.
This scribe note is based on the lectures of Professor Gauthier Gidel in Adversarial Machine Learning course , Winter 2022.
Services
Program Committee Member
- Mentorship and Networking Program Chair, Women in Machine Learning (WiML) workshop at NeurIPS 2024.
- Program and List of Mentors in three roundtable categories: Research, Life and Career Advice, and Sponsored.
Conference and Workshop Reviewer
- I reviewed for ICLR 2025, AISTATS 2024, ES-FoMO Workshop at ICML 2024 and ICML 2025, and Montreal AI Symposium 2024.