讲座题目：Date-driven risk analysis in freight transport systems

讲座时间：2023年9月25日（周一）19:00

腾讯会议：731-990-400

专家简介： Zaili Yang is Professor of Maritime Transport and Co-Director of Liverpool, Logistics, Offshore and Marine Research Institute at Liverpool John Moores University (LJMU), UK. He received his BEng in Maritime Transportation from Dalian Maritime University, China, in 2001, MSc in International Transport from Cardiff University, UK, in 2003, and PhD in Maritime Safety from LJMU, UK, in 2006. Prof. Yang’s research interests are analysis and modelling of safety, resilience and sustainability of transport networks, particularly maritime systems. Prof. Yang has received more than £7m external grants (£4m as the PI) from the EU and UK EPSRC, including a prestigious ERC consolidator grant. Prof. Yang has completed 10 postdoctoral and 37 PhD projects. He currently has 3 PDRAs and 9 PhD students under his supervision in the research areas of maritime safety and logistics operations. His research findings have been published in over 300 refereed papers in risk and transport areas, including 200 long journal papers (WoS citation: 5100, H-index:42; Google citation:8600, H-index:52). Prof. Yang is the AE/EMB of 14 journals (e.g. Transport Research Part E). He has received 14 paper awards (e.g. IMechE Journal Part M) and 5 research awards (e.g. Northeast Asia Logistics Award 2018).

报告摘要：Risk research represents an important challenge for the resilience and sustainability of freight transport systems (FTS) due to climate change, terrorism threats and an increasing amount of economic upheaval in the past decade. Its foci are being expanded from classical safety, through security to climate adaptation areas. Addressing risks of different features requires integration across disciplines and across research methodologies. Currently, we lack the critical understanding of which kinds of risk schemes can most effectively harness science and technology for achieving long-term resilient and sustainable FTSs. This presentation aims at introducing a series of studies on data driven risk analysis which enables the quantification, integration and communication of risk information from different areas and facilitates the movement of risk culture from a traditional reactive single dimensional scheme towards a new proactive multiple dimensional regime. The work will address the significant methodological issues associated with resilience and sustainability sciences particularly with reference to risk analysis under high uncertainty.