BEng (Traffic Engineering), MPhil (Transportation Planning & Management)
Hao’s primary research focus revolves around the recognition of driver states within automated vehicles. Specifically, his goal is to develop advanced artificial intelligence algorithms and models tailored for the classification and prediction of drivers’ drowsiness. Proficient in the Python programming language, he leverages its capabilities for data analysis, processing and modelling tasks. With practical expertise, Hao skillfully applies machine learning methodologies to tackle transportation challenges.
DOCTORAL RESEARCH
“Driver Drowsiness Classification of Automated Vehicles Using Attention-Based Multimodal Fusion”
THESIS SUPERVISORS
Dr Xiaomeng Li, Dr Mohammed Elhenawy, Professor Ronald Schroeter
RESEARCH INTERESTS
- Machine Learning
- Artificial Intelligence
- Driver States
- Automated Vehicles
AWARDS
- 2024 Australian Government Research Training Program (RTP) Stipend (International) and RTP Fees