Scientist Spotlight: Lauren Eliza Talbot
Written by Lauren Eliza Talbot
I am a PhD Candidate at U.C. Berkeley in Geotechnical Engineering, focusing on large-deformation numerical modeling in the Material Point Method (MPM). My research involves geo-interfaces and large-scale models such as landslides and dam failures, including visualization in Houdini. I work with fellow academics in the computational geomechanics section of the Soga Research Group.
During the bootcamp I created a virtual museum for the Lower San Fernando Dam Failure caused by the 1971 San Fernando Earthquake. The museum includes the background of the case study, well known in the field of geotechnical engineering, including historical information and past models of the failure. It then exhibits a MPM model of failure, completing a progression of research phases to the present. You can learn more about this MPM model from the Talbot et al. (2024) paper in Computers and Geotechnics.
I enjoyed immersing myself in the world of science communication and working with like-minded individuals, including those in 10k Science, expert panelists, and the other participants. It was wonderful to experience explanations of science well beyond my field of study and see how they were able to distill complex research into key concepts and an important overall message. I was, in turn, able to practice and improve my own presentation skills, especially necessary given no other geotechnical engineers participated.
The 10k Creator app itself opened up a whole new way to think about my research: how can someone intuitively interact with a spatial representation of the story I want to convey? I enjoyed being able to create a sense of the time period for various exhibits and embed information in these immersive spaces. Going through the experiences, there is a definite sense of exploration that far exceeds what I generally feel reading academic papers. The importance of this should not be underestimated: if the experience is memorable, it is far more likely to make an impact on the audience.
As a personal note, one of the things I love about my field and my research is the broad range of skills I have been able to bring into it: geotechnical engineering, geology, mathematics, numerical modeling, high performance computing, programming, technical writing, visualization, and science communication. I would like to personally thank my wonderful advisor, Professor Soga, for giving me the freedom to engage with them.
I have improved upon or taken up some of these throughout my PhD, both independently and through academic engagement, but still have much to learn in many fields. It was therefore a personal highlight of the bootcamp that I got to interact and work with professionals who have tremendous skills and experience in computer science and visualization. I cannot thank them enough for their help and hard work, particularly in creating whole new data transfer processes to get some of my computationally-expensive models into the app.
REFERENCES
Talbot, L. E. D., Given, J., Tjung, E. Y. S., Liang, Y., Chowdhury, K., Seed, R., & Soga, K. (2024). Modeling large-deformation features of the Lower San Fernando Dam failure with the Material Point Method. Computers and Geotechnics, 165, 105881. https://doi.org/10.1016/j.compgeo.2023.105881
Seed, H. B., Lee, K. L., Idriss, I. M., & Makdisi, F. (1973). Analysis of the slides in the San Fernando dams during the earthquake of Feb. 9, 1971 (73–2). College of Engineering, University of California.
