TRANSPORTATION · AI · OPERATIONS RESEARCH
Ph.D. researcher at the University of Sydney
I study how AI and operations research can improve urban mobility. My work combines reinforcement learning, network optimisation, and city-scale simulation to design more efficient, equitable, and resilient transport systems.
I am part of TransportLab in the School of Civil Engineering, supervised by Dr. Andres Fielbaum and Prof. David Levinson. My research draws on real-world demand and networks from Manhattan, Utrecht, and Canberra.
Transportation Research Part C: Emerging Technologies, 192, 105898.
A graph neural network actor–critic framework learns how strongly to anticipate future demand when routing and matching shared rides, with cross-city transfer from Manhattan to Utrecht.
Transportation Research Part C: Emerging Technologies, 187, 105645.
Choosing the last passenger’s drop-off with future trips in mind improves ridepooling service. The method combines sampled future demand with network structure and is evaluated in three cities.
Sustainable Cities and Society, 149, 107815.
Mixed-integer optimisation examines how charging needs and limited berth capacity affect electric-ferry schedules, using Sydney’s ferry network as a case study.
Feb 2024 — Present
The University of Sydney · Australia
School of Civil Engineering, TransportLab. Supervised by Dr. Andres Fielbaum and Prof. David Levinson.
Expected completion: mid to late 2027.
Jul 2019 — Jul 2023
Nanyang Technological University · Singapore
School of Electrical and Electronic Engineering.
UC Berkeley Summer Session, 2022: CS188 Artificial Intelligence and DATA100 Data Science.
Feb 2024 — Present
TransportLab, The University of Sydney
AI and operations research for on-demand mobility, with a focus on anticipatory routing, matching, and walking-enabled ridepooling. Since 2024, I have also contributed software and supervision to collaborative research on electric-ferry scheduling.
Feb 2025 — Present
The University of Sydney
Tutor for CIVL2700 Transport Systems (Semester 1, 2025) and guest lecturer for CIVL3704 (Semester 2, 2025), supporting quantitative analysis, computational methods, and Python-based modelling.
Jan 2025 — Apr 2025
TikTok · Sydney, Australia
Contributed to annotation and training-plan design for a vision-language model supporting video moderation. Developed Python-assisted data validation and coordinated annotation, training, and feedback across more than 20 policy areas.
Jul 2023 — Nov 2023
Farfetch · Shanghai, China
Delivered 5+ agile projects, primarily WeChat Mini-Programme development, for clients including MIDO, Ducati, Harrods, Baccarat, and Off-White. Coordinated requirements, design, engineering, testing, and client feedback, with completed projects generating more than US$100,000 in revenue.
Jun 2021 — Jan 2022
SenseTime · Singapore
Coordinated development and user acceptance testing for a computer-vision platform, translating requirements for baccarat-table supervision into scope, milestones, and validation cycles.
Feb 2021 — Jun 2021
Synthesis · Singapore
Developed Python models to forecast social-media trends and web crawlers to monitor keyword volumes and content evolution. Analysed high-dimensional textual data and delivered quantitative reports to support client decision-making.
Jun 2020 — Jul 2020
SWS Medical Group · Chongqing, China
Worked with senior software engineers to improve the interface and operating logic of haemodialysis machines using Go. Collaborated with mechanical engineers to test a new machine model before market launch.
Where should the last passenger be dropped off? Anticipatory walking in ridepooling.
Oral presentation · Toulouse, France
Anticipatory Methods in On-demand Mobility.
Oral presentation · Sydney, Australia
Optimizing Passenger Walking at Drop-off with Anticipatory Methods in Ridepooling Systems.
Oral presentation · Sydney, Australia
RL-based anticipatory routing and matching in on-demand ridepooling.
Poster presentation · Kyoto, Japan