Tri Ky Nguyen

Develop activity-based models, high-performance analytical tools, and data visualisation platforms for government transport planning projects. Led development of analytical frameworks using activity-based models for New Zealand and Victoria in a two-year project recognized as the most innovative project in the Australasia region in 2023. Design high-performance tools using Python, JavaScript, and Rust to process data efficiently for business case assessments and economic appraisals. Create dashboards, visualisations, and reports for projects including High-Speed Rail, Melbourne Airport, and major road infrastructure initiatives.

Conducted research on activity-based modelling and shared mobility systems while tutoring graduate and undergraduate courses in Traffic Engineering and Transport Engineering. Mentored student groups on final year projects related to intelligent transport systems. Worked on external projects related to smart cities and agent-based modeling using Melbourne Activity-Based Model (MABM). Developed deep learning models to predict parking bay occupancy rates.

Supported Melbourne Activity-Based Model (MABM) development and created user documentation. Helped predict changes in commuter behavior caused by growing demand, diverse travel preferences, and service disruptions.