Hi there, my name is Bo Lin (林博). I am a final-year PhD student at the University of Toronto. I am fortunately advised by Timothy Chan and Shoshanna Saxe. I also work closely with Erick Delage. I am affiliated with the Applied Optimization Lab and Sustainable Systems Research Group at UofT, and the Vector Institute. Prior to joining UofT, I completed my M.A.Sc. at the University of Waterloo. I did my undergrad at Tsinghua University.

I am interested in AI for sustainability. I develop predictive and prescriptive analytics tools that enable organizations to improve operational efficiency while promoting environmental wellness and the social good. With a particular focus on smart city operations and urban mobility, I address operational challenges from both practical and methodological perspectives. On the practical side, one line of my research involves developing data-driven approaches for urban bike network design, which I have applied to support Toronto’s 2025–2030 bike infrastructure planning. Our empirical findings have shaped policy decisions, leading to insights cited in policy documents and covered by mainstream media, including CBC News, Toronto Star, and UofT News. Motivated by challenges identified in this practical work, the other line of my research focuses on integrating machine learning and optimization, aiming to improve the efficiency, effectiveness, and applicability of data-driven decision-making tools.

My research has been recognized by several awards, including a finalist for INFORMS TSL Best Student Paper Award (winner TBD), a finalist for INFORMS Service Science Best Cluster Paper Award (winner TBD), a finalist for INFORMS DMDA Workshop Best Theoretical Paper Award (winner TBD), a runner-up for CORS Best Student Paper Award (Open Category), and NeurIPS Scholar Award.

In June-Sep 2023, I interned at Uber as an Applied Scientist, researching online marketplaces and advertising platforms. Here is a Uber Engineering Blog 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’m on the job market.

INFORMS Talks

• Conformal Inverse Optimization for Adherence-Aware Decision Prescription
  • Session: DMDA Best Student Paper Award (Theoretical Track)
  • Time: 2:30 - 3:45 PM, Saturday, October 19
  • Room: Summit 420/421
• Machine Learning-Augmented Optimization of Large Bilevel and Two-Stage Stochastic Programs: Application to Cycling Network Design
  • Session: ME35 - TSL Best Student Paper Award
  • Time: 4:00 PM - 5:15 PM, Monday, October 21
  • Room: Summit - 427
• Machine Learning-Augmented Optimization of Large Bilevel and Two-Stage Stochastic Programs: Application to Cycling Network Design
  • Session: ME49 - Data-Driven and Sustainable Mobility and Logistics System Design
  • Time: 4:00 PM - 5:15 PM, Monday, October 21
  • Room: Summit - 441
• Machine Learning-Augmented Optimization of Large Bilevel and Two-Stage Stochastic Programs: Application to Cycling Network Design
  • Session: TE06 - Service Science Best Cluster Paper II
  • Time: 4:00 PM - 5:15 PM, Tuesday, October 22
  • Room: Summit - 325
• Conformal Inverse Optimization for Adherence-Aware Decision Prescription
  • Session: WB31 - Learning for Contextual Optimization
  • Time: 12:15 PM - 1:30 PM, Wednesday, October 23
  • Room: Summit - 422

Contact

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