David Lallemant

PRINCIPAL INVESTIGATOR

Dr. David Lallemant

Prof. Lallemant joined the NTU faculty from Stanford University, where he was a researcher and founder of the Stanford Urban Resilience Initiative. He holds a PhD from Stanford University (2015), master’s degree from UC Berkeley (2010) and a bachelor’s degree from MIT (2007). His academic background is in earthquake sciences and engineering, predictive modeling, geostatistics, reliability analysis and others, used to conduct novel and impactful research to promote resilient societies.

Prof. Lallemant is also active in post-disaster response and recovery, which forms the basis for his research on post-disaster assessment and community resilience. He worked for two years in Haiti following the 2010 earthquake and has been involved with the response and recovery following the 2011 Christchurch earthquake and 2015 earthquake in Nepal. He regularly consults for the World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR).

His awards include the 2018 National Research Foundation Fellowship ($3M grant for 5-year research), the Shah Family Fellowship on Catastrophic Risk, the John A. Blume Fellowship in Earthquake Engineering, the Development Impact Award and the World Bank Vice Presidential Unit Award (for work conducted in Haiti).

RESEARCHTEACHINGVIEW PERSONAL SITECONTACT

Current Projects

My research covers the broad field of probabilistic risk analysis (aka mathematics of disasters), disaster risk reduction, post-disaster assessment and recovery. Spanning the entire disaster cycle, my research combines methods from spatial statistics, risk/reliability analysis, statistical learning and systems sciences in order to better understand the potential impact of disaster on society, and develop tools to promote resilient cities.

We work at the intersection of urban planning, engineering and statistics. My focus is on cities and urban regions as they represent extremes in terms of potential casualties and losses, and require more complex analyses due to their dynamics in terms of populations, infrastructure systems and networks.

UR Field Lab 2019:
Chiang Mai Urban Flooding

Informatics for Equitable Recovery: Mapping Recovery Need in Nepal

Developing Downward Counterfactual Methods for Disaster Risk Analysis

Quantifying Ecosystem Services for Flood Risk Reduction in Myanmar

Novel Methods for Modelling Disaster Risk

Improving Fragility Models and Uncertainty Propagation