MAPS 2024 Postgraduate (PhD) Innovation & Enterprise Student Prize Competition Winner Announced

The postgraduate (PhD) Innovation and Enterprise student prize was awarded to Kaiyu Li (UCL Statistical Science). The project was deemed to have an outstanding innovative aspect and a potential economic and societal impact. The competition aimed to motivate entrepreneurial spirit among the students.

Kaiyu Li - UCL Department of Statistical Science 

"MULTILEVEL METHODS FOR MONTE CARLO INTEGRATION, WITH APPLICATIONS TO TSUNAMI MODELLING"

Kaiyu's supervisor Professor Serge Guillas said: 

"It has been an immense pleasure to supervise Kaiyu Li, whose contributions have been essential to the delivery of novel tsunami risk assessments. Her work has enabled the estimation of economic impacts of future tsunamis onto the population of Indonesia, and the understanding of the uncertainties in the friction parameterisation over the terrain where the tsunami flooding happens - a key unknown in hazard assessments.

"Kaiyu created an efficient statistical surrogate model that samples future tsunami events based upon a set of simulations, and integrated these events into a catastrophe modelling platform. This required collaborative skills within a large and diverse team of experts: congratulations Kaiyu!"

In response to being awared the prize, Kaiyu stated:

"I am very grateful for the Innovation and Enterprise Award. This award is very timely as I am about to start my career in industry. It is an incredible honour and a strong encouragement and recognition of my work. I was fortunate to study under the supervision of Professor Serge Guillas and Dr François-Xavier Briol in the Department of Statistical Science.

"During my PhD, my research focused on developing novel multilevel methods and collaborating with scientists and economists to apply my research. It has been a pleasure to work on the application of my research to tsunami risk assessments, especially for humanitarian purposes over Indonesia.

"This collaboration demonstrates how Statistics can be used to better understand and mitigate risks. I also hope that some of the techniques I have introduced will further help businesses, agencies and NGOs deliver better tsunami hazard and risk assessments thanks to the efficiency of multi-level approaches to reach high resolution modelling at a low cost, and the benefit of taking into account uncertainties in friction coefficients to produce more realistic scenarios."