About

I am an R&D Engineer in the Department of Scientific Intelligence and Computing at the National Institute of Clean-and-Low-Carbon Energy (NICE) focusing on AI for Science. Before joining NICE, I was an assistant professor in the Department of Computer Sciences and Artificial Intelligence (School of Information Engineering) at the China University of Geosciences (Beijing).

I have hybrid backgrounds in geoscience and computer science. My primary research interests lie in utilizing data-driven methods to explore and address Earth-related problems, particularly those in paleoclimate and paleogeography. I have also been involved in projects related to geoscientific software development, quantitative stratigraphy, and spatiotemporal analytics. In addition, I was a participant of the Deep-time Digital Earth (DDE) project and co-founder of the GISphere Corporation.

I finished my Ph.D. at University of Wisconsin-Madison where I worked on EarthCube projects and was co-advised by Shaun Marcott and Shanan Peters. I hold a master’s degree from the University of Tulsa supervised by Bryan Tapp with a focus in computational geomechanics.

Education

• Ph.D. University of Wisconsin-Madison, Geosciences (Geoinformatics), 2018-22
• M.S. University of Tulsa, Geosciences (Computational Geomechanics), 2016-18
• B.S. University of Michigan, Earth and Environmental Sciences, 2013-15 & The Pennsylvania State University, Geographic Information Sciences, 2011-13

Teaching and Mentoring

I developed (from scratch) and taught the following new courses at China University of Geosciences (Beijing) from 2023 to 2024:

• SR043268: Introduction to Artificial Intelligence (100-level)
• DR040017: Data Analysis and Visualization (300-level)
• DR043229: Computer Vision (300-level)

At China University of Geosciences (Beijing), I supervised about 15 students majoring in software engineering, computer science, data science, and artificial intelligence in completing their theses. The topics spanned a wide range, including but not limited to:

• data-driven paleoclimate research
• deep learning for geoscientific data quality assessment
• development of interactive instructional tools for structural geology classes
• the modifiable areal unit problem in geological data analysis
• assessment of extreme weather and driving safety
• multimodal generative models for urban studies
• the application of artificial intelligence in music composition.

Before that, I held temporary lecturer or teaching assistant roles for the following courses:

• GEOL 4083: GIS for Geologists (University of Tulsa, as temporary lecturer)
• UC 270: Social Justice (University of Michigan, as teaching assistant)
• GEOG 363: GIScience (The Pennsylvania State University, as teaching assistant)