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EQUAL Lab
EQUAL Lab (EQuity & EQuality Using AI and Learning algorithms) is a cutting-edge research laboratory dedicated to advancing the fields of algorithmic fairness and responsible artificial intelligence (AI). With a mission to promote equity and equality in AI systems, Equal Lab harnesses the power of advanced learning algorithms and AI technologies to tackle the pressing issues surrounding bias and discrimination in machine learning models.
At Equal Lab, a team of multidisciplinary experts collaborates to develop innovative solutions that address algorithmic biases and ensure fair and ethical AI outcomes. Through rigorous research and the application of state-of-the-art techniques, the lab is at the forefront of reshaping the AI landscape to create more equitable and just algorithms.
Equal Lab’s research initiatives extend to various domains, including healthcare, finance, and beyond. By actively promoting privacy, transparency, accountability, interpretability and responsible AI practices, Equal Lab is paving the way for a future where AI technologies benefit all members of society, irrespective of their backgrounds or characteristics.
Open Opportunities
The EQUAL lab has two Ph.D. and one post-doc position at McGill University for Fall 2025, focusing on algorithmic fairness and privacy of deep learning and generative models. I do not hire master students for Fall 2025. If you have a solid background and keen interest in responsible AI and are excited about joining our lab, please apply through MILA’s request for supervision (deadline Decemeber 1, 2024)
Current students
Post-doc
- Afaf Taik, Post-doc, Mila, Fall 2022
- Florian Carichon, Post-doc, McGill, Summer 2024
PhD
- Aditi Khandelwal, PhD, McGill, Fall 2024 (co-supervision with Siva Reddy)
- Prakhar Ganesh, PhD, McGill, Winter 2023
- Mina Arzaghi, PhD, HEC Montreal, Fall 2023 (co-supervision with Jean-François Plante)
- Khaoula Chehbouni, PhD, McGill, Fall 2023
- William St-Arnaud, PhD, UdeM, Fall 2021 (co-supervision with Margarida Carvalho)
MSc
- Alireza Farashah, MSc, McGill, Fall 2024 (co-supervision with Negar Rostamzadeh)
- Marylou Fauchard, MSc, UdeM, Fall 2024 (co-supervision with Margarida Carvalho)
- Yash More, MSc, McGill, Fall 2023
- Armin Moradi, MSc, UdeM, Winter 2023
- Elahe Rahmati, MSc, Polytechnique Montreal, Fall 2022 (co-supervision with Thibaut Vidal)
- Rohan Sukumaran, MSc, UdeM, Fall 2022
Research Intern
- Aly M. Kassem, Full-time Intern, Winter 2025
- Sebastian Reinhardt , Full-time Intern, Summer 2024
- Saber Malekmohammadi, Full-time Intern, Summer 2023
- Cléa Chataigner, Full-time Intern, Summer 2024
Previous students
- Nicola Neophytou,Full-time Intern, Winter 2024 - Spring 2024
- Jesse Thibodeau, MSc, HEC, Fall 2021 - Summer 2024
- Raesetje Sefala, RA, McGill, Fall 2022 (co-supervision with AJung Moon)
- Mina Arzaghi, Full-time Intern, Summer 2023
- Nicola Neophytou, MSc, UdeM, Winter 2022 - Fall 2023
- Milan van den Heuvel, Post-doc visitor, Mila, Fall 2023
- Rebecca Salganik, MSc, UdeM, Fall 2021 - Fall 2023
- Kiarash Mohammadi, MSc, UdeM, Fall 2021 - Summer 2023
- Jia Ao Sun, MSc, UdeM, Fall 2020 - Summer 2023 (co-supervision with Esma Aïmeur)
- Maricarmen Arenas, MSc, HEC, Fall 2020 - Fall 2022 (co-supervision with Reihaneh Rabbany)
- Sikha Pentyala, Full-time Intern, Fall 2021 - Summer 2022 (co-supervision with Martine De Cock)
- Khaoula Chehbouni, MSc, HEC, Fall 2020 - Summer 2022 (co-supervision with Gilles Caporossi, Full-time Intern, Winter 2023 - Summer 2023
- Maryam Molamohammadi, Full-time Intern, Fall 2021 - Spring 2022 (co-supervision with Nicolas Le Roux)
- Giulia Occhini, Part-time Intern, Winter - Spring 2022 (co-supervision with David Rolnick)
- Raesetje Sefala, Part-time Intern, Winter - Spring 2022
- Amanda Leal, Part-time Intern, Winter - Spring 2022
- Allison Meyssonnier, MSc, HEC, Fall 2020 - Spring 2022 (co-supervision with Marie-Claude Trudel)
- Aisha Alaagib, Intern, Fall 2021 - Spring 2022 (co-supervision with Ulrich Aivodji)
- Amir Reza, MSc, UdeM, Fall 2019 - Fall 2021 (co-supervision with Laurent Charlin)
- Dylan Troop, Intern, Fall 2021
Prospective graduate students
Thank you for considering joining my group!
I am always looking for students to work with me in the areas of trustworthy machine learning, specifically fairness, privacy, robustness and explainability. Note that it’s very important that you and I are a good match. Once we start working together, we will be working very closely for at least 2 years (for M.Sc.) and 4 years (for Ph.D.).
I hire students at:
- the School of Computer Science at McGill University
- the Department of Computer Science and Operations Research(DIRO) at University of Montreal
First, check the department’s application deadline and make sure the start time you are about to email me is still feasible. For the Fall semester, if you are interested in doing a PhD, Master or internship with me, please apply first through the Mila admission website and put in your selection there that you are interested in working with me (Deadline December 1st). If your application is successful and passes the internal evaluation, I will contact you and invite you for an interview.
Second, note that it’s hard to evaluate your application by looking at your CV. In your email to express your interest in applying to work with me, please do the following.
- Highlight why you are interested in working with me. Check my research interests and read at least one of my recent papers and let me know which paper you read and ask one or more questions that came to your mind when you read it. Feel free to let me know what you liked/disliked about the paper;
- Highlight any research experience you have (if any);
- Highlight any scholarships you’ve been awarded or applied for
- A copy of your CV and transcripts
- A copy of a report, article, or paper you wrote (if any).
- For students with an advanced degree (e.g., Master’s), please mention who your Master’s thesis advisor is.
Note that I receive hundreds of requests like these and unfortunately I cannot guarantee to reply individually. However, I do review what you send me carefully. Please do not send me an email about your application more than once.
Funding opportunities
Below are links to various pages on funding opportunities in Montreal, just in case you didn’t know the info & opportunities are available.
Funding for Prospective Graduate Students
Students from Canada (residents/citizens)
- MITACS Scholarships
- IVADO scholarships
- Building 21 Fellowship
- Indigenous and Black Engineering and Technology Momentum (IBET) Fellowship (PhD)
Students from abroad
- Differential Fee Wavers for International Students (i.e., eligibility for Quebec tuition rate) Check the list of countries here.
- FRQNT Merit Scholarship Program for Foreign Students
- Links to more scholarships