EAWAG Subsurface Research Partnership: Advancing Machine Learning in Groundwater Risk Analysis
Our groundwater arsenic research partner, Dr. Joel Podgorski from the Swiss Federal Institute of Aquatic Science and Technology (EAWAG), visited our facility from March 31 to April 9. Dr. Podgorski is an internationally renowned scholar in the fields of groundwater quality and environmental risk assessment. His research focuses on leveraging advanced artificial intelligence and machine learning techniques for the spatial prediction and risk mapping of subsurface contaminants. During his visit, he delivered a keynote presentation titled "Machine Learning for Large-Scale Groundwater Quality Hazard and Risk Assessment and Associated Applications."
During Dr. Joel Podgorski's stay in Taiwan, Prof. Ching-Ping Liang from our Climate Change Groundwater Adaptation Research Team, along with Assistant Prof. Chia-Ju Chung from the Department of Computer Science and Information Engineering at National Central University, engaged in profound academic discussions regarding AI and machine learning applications. Technical presentations included a briefing by Dr. Thu-Yuan Nguyen on an AI/ML-driven surrogate model for multi-species transport (encompassing chlorinated solvent degradation products and radionuclide decay chains). Additionally, PhD Candidate Yu-Chieh Ho presented a 3D Taoyuan groundwater flow model developed using the specialized THMC software created by Chair Professor Gwo-Fong Ya at National Central University. Furthermore, first-year master's student Cheng-You Liu presented an AI/ML-driven surrogate model based on the 3D Taoyuan climate change framework, and Yu-Hsuan Zhan presented an AI/ML predictive model for groundwater nitrate tracking.
Dr. Podgorski served as the lead author alongside Dr. Michael Berg on a landmark paper published in the journal Science in 2020, titled "Global threat of arsenic in groundwater," which has secured over 1,296 citations, profoundly shaping global understanding of arsenic contamination hazards (Science DOI). EAWAG researchers (Kai-Yun Li, Joel Podgorski, and Michael Berg) also collaborated with our team at the Center for Advanced Model Research Development and Application (CAMRDA), including Adjunct Researcher Ching-Ping Liang, Director Sui-Sheng Chen, and Research Assistant Rui-Yu Zhang. This collaborative effort resulted in the 2026 paper primarily authored by Dr. Kai-Yun Li, titled "Groundwater arsenic in Taiwan: From Mid-20th-Century crisis to predictive models for risk mitigation strategies," published in the top-tier journal Environment International (Environment International DOI).
Special gratitude is extended to CEO Yen-Pu Hsu, who leads our National Science and Technology Council (NSTC) Proof of Concept (PoC) initiative, "Scientific Research Entrepreneurship Program: Multi-Application Services for Next-Generation Subsurface Environmental Simulation Software under Net-Zero Emissions and Water Environment Challenges," for his thoughtful arrangements and hospitality during Dr. Joel Podgorski's visit to Taiwan.
Empowering Subsurface Risk Mitigation with AI-Assisted Environmental Modeling
By integrating advanced machine learning architectures with conventional physical frameworks, our joint research initiatives pave the way for accelerated environmental management. Utilizing data-driven surrogate systems allows for rapid execution of heavy numerical constraints. This breakthrough translates into scalable benefits for engineering groups seeking predictive stability across multi-species decay pathways and regional Groundwater Contamination Assessment projects.