Bo Lin

Bo Lin

Postdoctoral Fellow

Conference Papers

  1. Conformal Inverse Optimization
    (with Timothy Chan and Erick Delage)
    NeurIPS'24 (acceptance rate: 25.8%)
    [Open Review] , [PDF], [5-min Talk], [3-min AI Podcast Intro]
  2. AutoLTS: Assessing Cycling Stress via Contrastive Learning and Spatial Post-processing
    (with Timothy Chan and Shoshanna Saxe)
    AAAI'24 (acceptance rate: 24.9%)
    [DOI], [PDF], [Code & Data]
    -  Preliminary version accepted to AAAI'23 Workshop on AI for Social Good

Journal Papers

  1. Machine Learning-Augmented Optimization of Large Bilevel and Two-stage Stochastic Programs: Application to Cycling Network Design
    (with Timothy Chan and Shoshanna Saxe)
    Minor revision, M&SOM, 2024
    [arXiv], [PDF], [Code], [5-min Talk] [12-min AI Podcast]
    -  Implemented to support Toronto's 2025-2030 bike infrastructure planning
    -  Winner, INFORMS 2024 TSL Best Student Paper Award
    -  Winner, NUS Analytics for X 2024 Best Student Presentation Award
    -  Runner Up, CORS 2023 Best Student Paper Competition
    -  Finalist, INFORMS 2024 Service Science Best Cluster Paper Award
    -  Finalist, 2024 Gilbert Laporte Student Paper Award
    -  Media Coverage: University of Toronto News, TechXplore
  2. Conformal Inverse Optimization for Adherence-aware Prescriptive Analytics
    (with Timothy Chan and Erick Delage)
    Major revision, Operations Research, 2024
    Preliminary: NeurIPS'24
    [SSRN], [Short Version], [Full Version], [5-min Talk], [60-min Talk], [3-min AI Podcast Intro]
    -  Finalist, INFORMS 2024 DMDA Workshop Best Paper Award - Theoretical Track
    -  Finalist, 2025 Gilbert Laporte Student Paper Award (Winner TBD)
  3. Exploring the Geographical Equity-Efficiency Trade-off in Cycling Infrastructure Planning
    (with Madeleine Bonsma-Fisher, Timothy Chan and Shoshanna Saxe)
    Journal of Transport Geography, 2024
    [DOI], [SSRN], [PDF]
    -  Media Coverage: University of Toronto News, TechXplore
  4. The Impact of COVID-19 Cycling Infrastructure on Low-Stress Cycling Accessibility: A Case Study in the City of Toronto
    (with Timothy Chan and Shoshanna Saxe)
    Findings, 2021
    [DOI], [PDF], [Data]
    -  Media Coverage: University of Toronto News, CBC News, Toronto Star
  5. Deep Reinforcement Learning for Electric Vehicle Routing with Time Windows
    (with Bissan Ghaddar and Jatin Nathwani)
    IEEE Transactions on Intelligent Transportation Systems, 2022
    [DOI], [arXiv], [PDF]
  6. Optimizing Electric Vehicle Routing and Charging/Discharging Under Time-Variant Electricity Prices
    (with Bissan Ghaddar and Jatin Nathwani)
    Transportation Research Part C: Emerging Technologies, 2021
    [DOI], [arXiv], [PDF]
  7. Text Mining Applications to Undergraduate Engineering Programs: Analyzing Differences in Gender, Nationality and Socio-economic Status
    (with Bissan Ghaddar and Ada Hurst)
    Likely a permanent working paper, 2021
    [arXiv], [PDF]

Work in Progress

  1. Analytics for Better Urban Cycling: A Multi-year Collaboration with the City of Toronto
    (with Madeleine Bonsma-Fisher, Timothy Chan and Shoshanna Saxe)
    -  Finalist, CORS 2025 Practice Prize (Winner TBD)
  2. Bridging Predictive and Prescriptive Analytics in Urban Cycling Network Design
    (with Timothy Chan and Shoshanna Saxe)

Collaborators

I’m fortunate to collaborate with, in alphabetical order, Madeleine Bonsma-Fisher, Tim Chan, Erick Delage, Bissan Ghaddar, Ada Hurst, Alexandre Jacquillat, Sheng Liu, Shoshanna Saxe, and Ian Zhu.

Open Source

Conference Presentations