Ben Cookson (Photo: provided)
Ben Cookson completed his MSc in computer science at the University of Toronto in March 2025. During his master’s studies in the Theory Group, he made a mark by publishing two papers in the AAAI Conference on Artificial Intelligence — a top conference in AI and social choice theory. Beyond his research, Cookson played a key role in fostering academic community by organizing the Theory Student Seminar, a student-led forum for sharing and discussing theoretical computer science research.
In this Q&A, Cookson reflects on his academic journey, the ideas driving his research and what lies ahead as he embarks on his doctoral studies.
This Q&A has been edited for clarity and length.
What initially drew you to the field of computer science, and how did you decide to pursue your MSc in CS at U of T?
I originally planned to become a software engineer, but during my undergrad I fell in love with the mathematical and theoretical side of computer science. By the time I graduated, I hadn’t done much research in theory, but I knew I’d regret not giving it a shot. That led me to apply to master’s programs focused on theoretical computer science. Once I was accepted to U of T, the decision was easy — Canada is a great country, Toronto is a great city, and U of T has an amazing CS department. I was especially excited by the research happening here in social choice theory.
What does social choice theory entail, and what got you interested in it?
Social choice theory studies how groups can make decisions when individual preferences differ. These decisions can range from organizing national elections to choosing a restaurant with friends. I find it incredibly cool because it combines everything I enjoy about theoretical computer science with ideas from economics, political science and philosophy, among other fields. Designing fair decision-making procedures requires creativity, problem-solving and deep mathematical thinking. But before you even get to that, you have to define what “fair” means in a given context, which is a fascinating challenge in itself.
What are some practical applications of your research?
My master’s research focused on resource allocation — figuring out how to fairly distribute items among people who all want them. I designed new algorithms for problems like dividing food donations among food banks or assigning shifts to nurses. More recently, I’ve been exploring how social choice theory can help design fairer AI systems. As we increasingly rely on AI to make decisions, it’s important to ensure those systems reflect people’s preferences in a fair and representative way. I think this is a really exciting and important direction for the field.
Who were your biggest mentors during your MSc studies?
I owe a lot to my advisors, Nisarg Shah and Allan Borodin. They took a chance on me when I had little research experience in theoretical computer science and have been incredibly supportive ever since. They gave me interesting problems to work on, helped me navigate the research process and offered great advice on managing grad school. Beyond that, the CS department and Theory Group have cultivated a fantastic culture. Every faculty member I’ve interacted with has been kind, helpful and encouraging.
What advice would you give to future MSc students in computer science at U of T?
Grad school is fun and rewarding, but it’s also hard. Producing good research takes persistence, long hours and sometimes a bit of luck. You’ll have ideas that don’t work out, and that’s okay — it’s part of the process. Talk through everything with your advisor, take their advice seriously, but also don’t be afraid to explore your own ideas. One of the most valuable things you can learn in a master’s is how to generate novel ideas and creative solutions to problems.
Since graduating with your master’s degree in March, you’ve stayed on in the department as a PhD student. What motivated that decision, and where do you see your research journey taking you in the future?
Just like joining U of T for my MSc, deciding to stay for my PhD was one of the easiest decisions I’ve ever made. I love what I do and am very happy I get to continue doing it for a few more years. Right now, I think I’d like to try for a position in academia after I graduate, but I still have some time to figure out exactly what my plans are.