معرفی
Angelo D'Elia is a Research Fellow at the Monash University Accident Research Centre (MUARC) and a Statistical Consultant at the Victorian Injury Surveillance Unit (VISU). He holds a PhD in Public Health and Honours degrees in Mathematical Statistics and Mechanical Engineering. His expertise spans road safety evaluation, vehicle safety research, data linkage, and injury prevention. He leads and contributes to over 40 research projects, focusing on crash data analysis, countermeasure effectiveness (e.g., speed enforcement, airbags), and trauma trend modeling. D'Elia has authored 68+ publications and received awards for his work, including the 2024 Peter Vulcan Best Paper Award. He advises PhD students and collaborates internationally, contributing to policy through expert submissions to government inquiries.
- Education:
- Doctor of Philosophy in Public Health
- Bachelor of Science (Honours) in Mathematical Statistics
- Bachelor of Engineering (with Honours) in Mechanical Engineering
Research Interests: Angelo’s work centers on optimizing administrative data for injury prevention, evaluating road safety programs (e.g., automated enforcement, vehicle safety tech), and developing advanced statistical models. He emphasizes translating data into actionable insights for policy, such as real-time injury tracking systems and baseline trauma models.
Articles Trends: Recent work highlights vehicle safety regulations, injury severity scoring via linked data, and pandemic impacts on road safety. His analyses often combine large-scale datasets with time-series modeling to identify trends and inform policy.
- Awards:
- Peter Vulcan Best Paper Award (2024)
- MIRI Award for Best Early Career Paper (2013)
Advising & Grants: Accepts PhD students and leads major grants evaluating NSW automated enforcement programs, crash avoidance technologies, and vehicle safety innovations. Collaborates with MUARC teams and external agencies on road trauma reduction initiatives.
Labs/Teams: Member of the Injury Analysis and Data team at MUARC and VISU, focusing on statistical methodologies and interdisciplinary road safety solutions.
