Risk and Resilience Management
ラム研究室 LAM Laboratory
准教授：ラム チ ユン（LAM Chi Yung）
Risk Engineering, Disaster Prevention, Critical and Social Infrastructure Protection
Risk, Disaster, Resilience, Infrastructure, Analysis, Simulation
We welcome students with a good class degree in engineering or science, and interest/experience in numerical and data analysis. Good written and oral communication skills in English are also required.
Students who graduate from our laboratory will acquire knowledge and skills regarding recognizing, assessing and managing the impacts of emerging and systemic risks in society. We are concerned with catastrophes and how their impacts are nonlinearly cascaded, students will then gain understanding of methodologies and integrated analytical techniques underlying the existence of various interdependencies and complexities across our society.
【就職先企業・職種】 Civil servant, consultant company, railway/ transportation/ engineering company
We are conducting research on modeling, analysis, and prediction of risk cascades and resilience in infrastructure and socioeconomic systems, including (but not limited to):
Fig. 1. Sets of incident/accident chains and their transformed interdependent network (with probabilities and impacts).
Fig. 2. Predicted time-series changes of risk level and the cascading pathways of disastrous effects in areas.
Risk Cascade Analysis and Prediction
We have applied statistics and probabilistic models to quantitatively identify the effects of various risk factors and its cascading pathways in infrastructure systems and socioeconomic systems. Complex network modeling and big data analysis approaches are adopted to capture the nonlinear complexity of the interdependencies among multiple causes and multiple results, so as to reveal the causation of catastrophes on how and whether changes in the risk factors propagate to effects (Fig 1).
Resilience to Risks and Disasters
Resilience refers to the ability to recover from the adverse effects. We have integrated information science with planning and management science to model the impacts of risks and disasters, and to develop new evidence-based decision-making support systems for societies with greater resilience to risks and disasters. This research area explains the observed associations and sequences of change mechanisms between risk factors and effects, so it covers the study of prevention, preparedness, response, and recovery and restore from risks and disasters (Fig 2).
- LAM, C.Y., et al. (2021). Topological network and GIS approach to modeling earthquake risk of infrastructure systems: A case study in Japan. Applied Geography, 127.
- LAM, C.Y., et al. (2020). Network topological approach to modeling accident causations and characteristics: analysis of railway incidents in Japan. Reliability Engineering & System Safety, 193.
- LAM, C.Y., et al. (2019). Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan. Reliability Engineering & System Safety, 185.
Advanced analytical software and analyzers, high performance computers, smart glasses.
We encourage students to conduct advanced research based on their interests. We motivate students to work hard while enjoying
their time in our laboratory.