Completed Journal Papers

1. Analytics for Better Urban Cycling: A Multi-year Collaboration with the City of Toronto
   (with Madeleine Bonsma-Fisher, Timothy Chan and Shoshanna Saxe)
   To be submitted, 2025
   -  Winner, CORS 2025 Practice Prize
   -  Semi-finalist, INFORMS 2025 Daniel H. Wagner Prize (Winner TBD)
   
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
   
3. 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
   
4. 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
   
5. 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
   
6. 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]
7. 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]
8. 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]
   

Conference Papers

1. Conformal Inverse Optimization
   (with Timothy Chan and Erick Delage)
   NeurIPS'24
   [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
   [DOI], [PDF], [Code & Data]
   -  Preliminary version accepted to AAAI'23 Workshop on AI for Social Good
   

Work in Progress

1. Bridging Predictive and Prescriptive Analytics in Urban Cycling Network Design
   (with Timothy Chan and Shoshanna Saxe)
   

Open Source

• AutoLTS: Computer vision models to assess cycling stress of road networks:  
• LTS-TRT: The level of traffic stress network in the City of Toronto (July 2021):  
• R2D-VRP: A hierarchical reinforcement learning framework for solving the vehicle routing problem :  
• OCT: Python implementations of optimal classification tree formulations and their computational performance:  
• CycleLinx: An interactive web app for exploring Toronto’s bicycle network and our optimized expansion plan: