About me 👋
“What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
— Herbert A. Simon, Economist and Nobel Laureate
Hi there, I’m Jungang (Gordon) Chen 🐳
I’m currently a Postdoctoral Fellow at the Bureau of Economic Geology, Jackson School of Geosciences, University of Texas at Austin.
My current duties include:
- Leading the development of newest version of EASiTool – a Python-based CO₂ storage capacity estimation platform that is trusted and used by >100 professionals from industry, government, and academia.
- Employing and developing machine learning algorithms to improve the description, prediction, and control of subsurface systems, with a particular focus on carbon capture and storage (CCS).
I obtained my Ph.D. in Petroleum Engineering in 2024 from Texas A&M University, where my research focused on numerical simulation, scientific machine learning, deep learning-based surrogate modeling, and reinforcement learning applications. Before that, I earned an M.S. in Petroleum Engineering from the University of Southern California.
Outside work, I enjoy exploring Foundation models, AI agents, and coding– and I love playing tennis 🎾.
My research interests include:
- CCS, computational geoenergy, machine learning
- Integration of domain knowledge with AI/ML to advance sustainable energy solutions
- Development of reproducible, open-source tools for reservoir modeling and CO₂ storage assessment
Feel free to explore my site to learn more about my projects, publications, and teaching.