tl;dr
Thank you for your interest in working with me. I receive many emails regarding joining the Adaptive Agents (Adage) Lab. I wish I could answer all of them in detail, but unfortunately I cannot. Please don’t take it personal! Instead, I present you with a FAQ. Hopefully my explanation here answers most of your questions.
Graduate Students: I will recruit 1-2 new students for the academic year 2025-2026 (September 2025) at Polytechnique Montréal and Mila. Start by filling the Supervision Request of Mila before December 1, 2024.
Undergraduate Students, Interns, Visitors, Postdocs, etc: I may take trainees for 2025 at Polytechnique Montréal, but the detailed plans are not decided yet. Stay tuned!
Graduate Students
Q: Will you recruit any new graduate students for the academic year 2025 (Fall)?
A: Yes, 1-2 students at Polytechnique Montréal and Mila. This year I most likely recruit someone who will work on the RL Algorithm/Theory.
To apply, you need to fill the Supervision Request of Mila before December 1, 2024. You also need to apply to PolyMtl, if I shortlist you for interview.
Q: Will you become my supervisor or help me in the admission process?
A: Admission is granted by the university, and not by me. I will have a say on whether I am interested in a particular applicant or not! I will decide on whether or not I am interested in working with a student only after seeing all the applicants and looking at their files closely. This will happen in early Winter (January-February). Unless you are really an exceptional match (you have already published 2-3 very good papers in my research area in top venues such as NeurIPS or ICML and I know you personally), I cannot really provide a more concrete answer before then.
Q: How can I ensure that you look at my application?
A: When you fill the Supervision Request, there is a field in the application where you can specify your interest in working with faculty members. If you write my name, I will look at your application.
Q: Do you mind if I contact you meanwhile?
A: No, but it may not be needed! FYI, approximately half of all offers initiated by me in the past 4 years were to students who hadn’t contacted me beforehand. I cannot definitely claim their emails didn’t have any effect at all (I need more data!), but I believe sending email is not a must for me.
I will go through all applications that mention my name, one by one, no matter whether you email me beforehand or not.
If this isn’t comforting enough for you, and if you think we are really a good match, feel free to send me a note. But please don’t take it personal if I don’t reply back. I probably won’t, and it is not because I want to be rude, but because if I reply back all emails, I will lose a lot of time that I could spend on research and working with my students (so, please don’t follow up if I have read your email; I have probably read it). Just make sure to mention my name in your application. That is the best way to guarantee that I look at your application. If you want to contact me regarding admission nonetheless, please write KnoReG Machine in your subject line. This indicates whether you have actually read this page.
Q: I have a limited budget to apply to many universities. I won’t apply unless I know there is a good chance. Can you help me with this?
A: The good news is that this problem is partially solved here! Applying to Mila is free, so I can see your application and compare it with all other applicants, before you even apply to the university. If I shortlist you and decide to interview you, you need to apply to Polytechnique Montréal. Being shortlisted is not a guarantee for getting admission, but at least you know you have passed the screening.
Q: How should I know if we are a good match?
A: Generally speaking, I am looking for a student who is an independent thinker, mathematically mature, organized, self-motivated, has a solid ML/RL background, has some research experience, knows how to write good code, and is a joy to work with. Please take a look at my research and papers to get a better idea of my research style (and don’t look only at the last paper as it may not be the representative of my work) and my Research Statement: Rethinking Reinforcement Learning.
Mathematics: My research is mathematical theory-inclined, so you need to have a strong background in math and computer science, and enjoy approaching ML/RL problems from the mathematical perspective. In practice, this mean that in my team we often write down formulae on a paper or whiteboard (or iPad) first, think hard about them, mathematically analyze them, and maybe even prove some of their properties, before writing an extensive codebase and empirically studying them (this is not always the case, but should give you an idea).
You need to feel comfortable working with probability theory, linear algebra, calculus, etc. You also need to have experience proving theoretical results and be mathematically “mature”.
Note that I do not require you to be a math major or have taken many math courses, but I need to get a sense that you can do a math-heavy research.
RL and ML background: You need to have a solid background in ML and RL. For example, you need to have taken some relevant university courses or carefully read a good part of a standard textbook. For RL, Sutton and Barto is a good book, but my approach is more mathematical, so maybe take a look at my own textbook Lecture Notes on Reinforcement Learning.
Research experience: Research experience is very desirable. Good MS students have some research experience in their undergrad. I expect someone who applies for a PhD program after their MS program (as opposed to direct PhD from their undergrad) to have prior experience in conducting an independent and original research and writing a manuscript in ML/RL-related topic, and ideally some publications in good venues (such as NeurIPS, ICML, etc.). If you have not published a paper yet, but you have a manuscript of the top quality, it might be acceptable to me.
Application of an ML algorithm to a standard dataset, though very appropriate for a homework or even a course project, is usually not what impresses me as the research experience.
Programming: You need to be able to implement your ideas quickly, clearly, efficiently, and correctly. Even my theoretically-inclined students should be able to program. If you have an online code repository, make sure to include it in your CV.
The standard for a PhD student is higher than for an MS student. For example, an MS graduate needs to have research experience and published papers in areas close to what I do.
Q: What is the probability of my admission?
A: It is a conditional probability after all, and part of the condition is you, and another part is others in the pool. I cannot honestly give you any good estimate. Just know that Mila receives a lot of applications, and many of them are strong. Unfortunately our resources are limited, so we can only accept a limited number of students. I estimate that tens of students show interest in working with me. This is my privilege, and I acknowledge it. Unfortunately, I can only recruit a very limited number of students per year, perhaps only one or at most two, so that I keep my group size relatively small. As a result, the prior probability of being accepted to work with me is low. Note that there are many great professors affiliated with Mila in Quebec, so you should definitely consider them when you apply. This increases your chance. But overall, the chance of admission is low. I understand this is unfortunate and many great students may not get admitted at the university they wish. You need to know that the admission process can be quite noisy, so if you don’t get admitted, don’t consider it as a judgment on you or your ability.
Q: What will happen after I apply?
A: Many things happen at Mila and at Polytechnique Montréal. Since I am new to both, I do not know the exact timeline of the events, but it is more or less as follows. I also try to give you an estimate about what percentage of applicants go through each stage. These numbers are very approximate, and may not present an accurate estimate of what happens this year. It may give you some ideas about what to expect nonetheless.
+ After you apply to Mila by filling the Supervision Request form before December 1st, your application goes through Mila’s internal process. I will have access to your application at the end of December or early January.
+ I will go through all those who have mentioned my name. I will read their applications (look at their CVs, transcripts, reference letters, SOP, etc.), and will give them a rough score based on their GPA, courses taken, research experience, language skills, letters of reference, etc. This happens in January. This leads to my long shortlist. In previous years, the long shortlist consisted of about 10-25% of the applicants who mentioned my name in their applications.
+ I start the conversation with the applicants in my long shortlist through email (mid/late January), and may assign some small tasks such as reading a paper and summarizing it. If I see a good potential and match based on this information, but before the interview, I encourage them to apply to the Department of Computer and Software Engineering at PolyMtl and mention my name in their application. This would be my shortlist. The percentage of students in the long shorlist who got to the shortlist in previous years was about 30%.
+ I have video chat with the shortlisted applicants (late January or early February), and perhaps even ask them to give a short 10-15min talk about their current research (if they have done some previous experience) or about a paper that they read. I ask both technical questions as well as try to figure out their research interests and whether there is a good personality match. This step of interview may take 1-2h. After processing all applicants, I choose one or two (20-30% of the shortlist) and I will express my interest in working with them to the department. The admission committee considers my recommendation in making their final decision. In the case that an applicant does not accept my offer, I may extend an offer to other students in the shortlist. This means that it may take a while before hearing a definite answer at this stage.
Q: Why don’t you admit more students?
A: Two of my main resources are 1) time and 2) funding. Both are unfortunately bounded (you have less than 1M hours in your life, if you live a very healthy life and you are lucky). Even if I have an unlimited amount of money, I don’t have unlimited time to advise and guide my research group. Having more students means that I have to spend less time with each of them, which reduces their productivity, and is not fair to them. Moreover, it means that I cannot get involved in their research as much as I like. And I like to be involved in their research – that’s the point of being a researcher after all. At the moment, I plan to have a team of 3-6 graduate students.
Q: I am an undergraduate student. Should I apply to the Master’s or PhD program?
A: If you are an international student, do not apply to the Master’s program, but directly apply to the PhD program (why? keep reading!). If you are an undergraduate domestic student, apply to the Master’s program. My preference is that a domestic student starts as an MS student, but comes with the intention of working towards a PhD. The reason is that the PhD program allows more time to do good research and get deep into a topic. An MS student and I work for 2 year together, and if we are both happy, the student transitions towards PhD. But if you really don’t want to do a PhD, that can be discussed, but please be upfront.
The reason I am suggesting international students to not apply to the MS program is because of how the funding system works. The tuition for the Master’s student would be unreasonably high. Unless an international MS student has an extenal source of funding, the funding provided by the university would not be enough to cover the living expenses.
Q: What is the relation between Polytechnique Montréal and Université de Montréal?
A: PolyMtl is the engineering school of UdeM. When you get your PhD, you have the logo of UdeM and PolyMtl at the top of your PhD certificate.
Q: Do I need to know French?
A: No, but knowing or learning a bit of French will make your life easier. PolyMtl is a French school, so communication from the admins will be in French. Most graduate courses in AI/ML are in English, and you can choose the courses across different universities in Montreal. See the list of courses for 2024 here, which also indicate which of them are offered in English or French. Since you will be located at Mila, your research environment will be in English, with bilingual communication from admins. Knowing some French in Montreal allows you to enjoy the city even more.
Q: Should I apply for external funding?
A: Yes, if possible. If you are a domestic student, I encourage/expect you to apply for government fundings such as NSERC or similar in Quebec. If you are an international student and there are similar scholarships in your country, apply for them. Note that having a funding is not a guarantee for your admission, but it removes or relaxes some constraints. What is most important is that we are a good match and can do good research together.
Q: Who else do you recommend if I want to work on AI/ML/RL?
A: There are many excellent researchers around the world working on AI/ML/RL. Let me focus on Canada first. Look at the academic members affiliated with Mila – Quebec Artificial Intelligence Institute to know many PIs in Quebec who works on AI/ML (the list is not exhaustive). Mila is one of the three Canadian centres for AI research. The other two are Amii (which has a particularly strong program in RL) and Vector Institute. There are several other excellent professors at other Canadian universities too, who are, for whatever reasons, not part of these institutes. For the list of RL researchers at the global level (with a focus on North America), take a look at this spreadsheet (maintained by Philip Thomas).
Undergraduate Research and Internships (Graduate or Undergraduates)
[Currently (Fall 2024) I will not recruit any new student or trainee for Fall 2024 or Winter 2025, but I may recruit for Summer 2025.]
I recruit undergraduate students who are interested in doing research as well as undergraduate or graduate-level interns. You will probably work closely with one of my PhD students.
+ Polytechnique Montréal: I may recruit undergraduate students, but probably not immediately. I will announce my plans here.
+ University of Toronto: I won’t be recruiting students at the U of T anymore.
+ Outside Canada: Not at this point.