SangHyung Ahn

SangHyung Ahn is Lecturer in the School of Civil Engineering. SangHyung Ahn joined UQ in 2015 as postdoctoral research fellow and started working as Lecturer in 2017 after pursuing his PhD research in Civil Engineering (Construction Engineering and Management) at Purdue University in USA. Prior to joining Purdue, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (ranked as world’s top 15 international contractor in Engineering News-Record 2015) from 2003 to 2007. He also holds his MBA (international business) from Hanyang University in South Korea and his B.Sc (Civil Engineering) from Korea University in South Korea. Dr. Ahn’s research focus encompasses construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and construction management systems with Building Information Modelling (BIM). He is currently coordinating and delivering undergraduate courses, Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) offered in the School of Civil Engineering at UQ. Construction operations modelling, simulation and visualisation; Automation for construction operations analysis, data collecting, and simulation modelling process; Scalable analytics (data mining and process mining); Analytics presentation (information visualisation and animation in 3D); Sensing (remote sensing and multi-sensor systems); Building Information Modelling (BIM); Decision making in complex systems and knowledge management

[2026] Journal Article: Interpretable data-driven driver behaviour modelling with adversarial inverse reinforcement learning. Lin, Lin, Kim, Jiwon, Sun, Jie and Ahn, Sanghyung (2026). Interpretable data-driven driver behaviour modelling with adversarial inverse reinforcement learning. Artificial Intelligence for Transportation, 7 100064, 1-23. doi: 10.1016/j.ait.2026.100064 [2023] Conference Publication: Interpretable data-driven car-following modelling with adversarial inverse reinforcement learning. Lin, Lin, Kim, Jiwon, Sun, Jie and Ahn, Sanghyung (2023). Interpretable data-driven car-following modelling with adversarial inverse reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2023.