Hi there, my name is Bo Lin (林博). I am a PhD student at the University of Toronto. I am fortunately advised by Dr. Timothy Chan and Dr. Shoshanna Saxe. I also work closely with Dr. Erick Delage. I am affiliated with the Applied Optimization Lab and Sustainable Systems Research Group at UofT, and the Vector Institute. I was a Visiting Student Researcher at Mila. Prior to joining UofT, I completed my M.A.Sc. at the University of Waterloo where I worked with Dr. Bissan Ghaddar and Dr. Jatin Nathwani. I obtained my B.Eng. at Tsinghua University.

In June-Sep 2023, I interned at Uber as an Applied Scientist, researching online marketplaces and advertising platforms. Here is a blog post that introduces what I did at Uber. In Jan-Aug 2022, I was a research intern at Esri Canada under the SMART Mobility projects.

I am interested in sustainable operations, with a primary focus on transportation systems to date. I design scalable and implementable optimization and machine learning algorithms that improve transportation efficiency, environmental wellness, and the social good. My research has been covered by CBC News, Toronto Star, UofT News, and Uber Engineering Blog.

News

• 04/2024: A poster accepted to the Princeton Workshop on Optimization, Learning, and Control
• 04/2024: Our paper Machine Learning-Augmented Optimization of Large Bilevel and Two-stage Stochastic Programs: Application to Cycling Network Design has been selected as a finalist for the inaugural Gilbert Laporte Student Paper Award.
• 02/2024: Attending AAAI this week. See you in Van!
• 01/2024: New Pre-print: Conformal Inverse Optimization.
• 01/2024: New Pre-print: Exploring the Geographical Equity-Efficiency Tradeoff in Cycling Infrastructure Planning.
• 12/2023: Our paper AutoLTS: Automating Cycling Stress Assessment via Contrastive Learning and Spatial Post-processing has been accepted to AAAI-24!
• 10/2023: Check out this blog post Accelerating Advertising Optimization: Unleashing the Power of Ads Simulation that introduces what I did at Uber.
• 05/2023: Our paper A Machine Learning Approach to Solving Large Bilevel and Stochastic Programs: Application to Cycling Network Design won Runner Up for the CORS 2023 Student Paper Competition (Open Category).
• 02/2023: I’ve been awarded the DiDi Graduate Award.
• 02/2023: I’ll join Uber as an applied scientist intern this summer. See you in San Francisco!

Contact

• Dept. of MIE, Faculty of Applied Science & Engineering, University of Toronto
• Email: blin AT mie DOT utoronto DOT ca