Working with Me

My research sits at the intersection of machine learning and operations research. I work on operational problems that enable and accelerate AI development and deployment: how training data is collected and annotated, how models are evaluated, priced, and put into practice. More recently, I have become interested in AI agents and the operational and social challenges that come with deploying and using them.

Prospective Students, Postdocs, and Interns

Graduate students (MSc & PhD). I supervise students at the University of Ottawa through several programs: the PhD in Management and the MSc in Business Analytics at the Telfer School of Management, Digital Transformation & Innovation (MSc/PhD), and Systems Engineering (MSc/PhD). If you are interested in working with me, especially if you are international or not currently at the University of Ottawa, send me an email with your CV and transcript, and mention which program(s) you are considering. This makes it much easier for me to advise you on next steps.

The applications that catch my attention show that you have actually read my recent papers and have something to say about them (see my publications): a specific observation, an extension you would be excited to pursue, or a question the work left you with. This tells me far more about how you think than any summary of your background.

Please do not send emails that only list your background, echo keywords from my research, or mention a paper or two without engaging with them. These are indistinguishable from mass emails. I read every application I receive, but I receive more than I can reply to individually, and emails of this kind are unlikely to receive a response.

Undergraduates at the University of Ottawa. If you are curious about research, feel free to reach out and we will find a time to meet.

Postdoctoral researchers. Send me an email with your CV and a few of your published papers, along with how you see your work connecting to mine.

NVIDIA research internships. I typically work with 1–2 research interns per year at NVIDIA. Nearly all are PhD students in progress, with at least one publication at a major ML conference relevant to my NVIDIA research (see my recent publications on data curation, evaluation, and autonomous driving). If you see a fit, email me at NVIDIA and explain how.

What I Expect

Research in this space draws on three toolkits: machine learning (especially LLMs and, increasingly, agentic systems), operations management modeling (inventory, supply chains, pricing), and applied mathematics (mainly probability and mathematical optimization). I don’t expect expertise in all three; strength in at least two, and the willingness to pick up the third, is the typical profile. Strong programming skills are essential, including AI-assisted development.

Above all, I expect high agency. Execution has become cheap since AI tools can write code, run experiments, and draft text. What matters now is idea generation, judgment, and design decisions: coming up with questions, exploring methods, keeping pace with a fast-moving literature, and recognizing when an approach isn’t working and figuring out why. If you are curious and show independent thought, we will work well together.