Bright Spark Lectures: 4th Workshop on Future of Machine Learning in Geotechnics (FOMLIG), Seoul
Jiawei Xie, Professor at the School of Infrastructure Engineering, Nanchang University, Nanchang, China
Bright Spark Lecture title: “Seeing the Unseen: From Sparse Observations to Cognitive Subsurface Modelling”
Dr. Jiawei Xie is a recipient of the 2025 National Outstanding Young Scientists Fund (Overseas). He previously served as a Research Associate (Level B) at the University of Newcastle, Australia, where he earned his Ph.D. following studies at Central South University. His research focuses on data-intelligent subsurface characterization, 3D ground modeling, and risk assessment, contributing significantly to two ARC Discovery Projects and multiple industry projects for the Australian Rail Track Corporation (ARTC). Dr. Xie has published more than 30 SCI journal papers in leading journals such as Engineering Geology, Geoscience Frontiers, and Tunnelling and Underground Space Technology. His work has been recognized with the 2022 ISGSR Best Paper Award and the 2024 NSW Research Award Nomination (top 5 finalists). In terms of technology transfer, he developed the RockMapper software and open-source GitHub systems like Rock-Camera and CrackGen; his “Intelligent Geological Prediction System” won the Excellence Award in the "Chunhui Cup" Innovation Competition. He serves as a session chair for ISGSR, ISRERM, and 5MLIGD, and holds youth editorial roles for Geotechnical Engineering and Frontiers in Earth Science while regularly reviewing for top journals including Géotechnique and IJRMMS.
Yongjin Choi, Postdoctoral Fellow, Korea Advanced Institute of Science & Technology, Seoul, South Korea
Bright Spark Lecture title: “Differentiable graph neural network simulator for accelerating granular flow geohazard modeling”
Dr. Yongjin Choi is a Postdoctoral Fellow at the InnoCORE PRISM-AI Center at KAIST and an Affiliated Researcher in the School of Civil and Environmental Engineering at Georgia Institute of Technology. He will join the Department of Civil and Environmental Engineering at the University of Massachusetts Amherst as an Assistant Professor in September 2026. He received his Ph.D. in Civil Engineering from The University of Texas at Austin, with a dissertation on forward and inverse modeling of granular flows using differentiable graph neural network simulators, after earning his B.S. and M.S. from Pusan National University. His research develops physics-aware machine learning and scientific computing methods for geotechnics, with emphasis on AI-accelerated geohazard modeling and inverse analysis, uncertainty quantification, AI-aided automated hazard detection, and differentiable simulations. His work has led to publications in leading geotechnical and computational engineering journals, such as Computers and Geotechnics, Soils and Foundations, and Computer-Aided Civil and Infrastructure Engineering. He has also delivered invited lectures on physics-aware AI for geotechnical modeling and received the Young Scholar Award from the Korean Geotechnical Society.