Research Roadmap
- AI for Sustainability
- Urban Bike Infastructure Planning (Ph.D. Thesis) [1, 2, 3, 4, 5, 6, 11]
- Integration of Electric Vehicles and Power Systems [7, 8]
- Equity, diversity, and inclusion in higher education [9]
- Integration of Machine Learning and Optimization
- Optimization for Machine Learning [1, 4, 10]
- Machine Learning for Optimization [3, 7, 11]
Conference Papers
- 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]
- NeurIPS Scholar Award, 2024
- 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
- Machine Learning-Augmented Optimization of Large Bilevel and Two-stage Stochastic Programs: Application to Cycling Network Design
(with Timothy Chan and Shoshanna Saxe)
Major 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 (1/40)
- Winner, NUS Analytics for X 2024 Best Student Presentation Award (1/17)
- Runner Up, CORS 2023 Best Student Paper Competition (2/31)
- Finalist, INFORMS 2024 Service Science Best Cluster Paper Award (9/50)
- Finalist, 2024 Gilbert Laporte Student Paper Award (3/9)
- Media Coverage: University of Toronto News, TechXplore
- Conformal Inverse Optimization for Adherence-aware Prescriptive Analytics
(with Timothy Chan and Erick Delage)
Under review, 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 (8/50)
- 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
- 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
- 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] - 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] - Text Mining Applications to Undergraduate Engineering Programs: Analyzing Differences in Gender, Nationality and Socio-economic Status
(with Bissan Ghaddar and Ada Hurst)
To be submitted, INFORMS Transactions on Education, 2024
[arXiv], [PDF]
Work in Progress
- Contextual Risk Measures
(with Timothy Chan and Erick Delage)
Work in progress, 2024+ - Bridging Predictive and Prescriptive Analytics in Urban Cycling Network Design
(with Timothy Chan and Shoshanna Saxe)
Work in progress, 2024+
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:
Conference Presentations
- INFORMS: 2020, 2022, 2023, 2024
- CORS: 2019, 2021, 2022, 2023, 2024
- AAAI: 2023, 2024
- Vector Research Symposium: 2023
- TRB: 2024
- POMS-HK: 2024
- MSOM: 2024
- ISMP: 2024
- NeurIPS: 2024
