Browse public teaching materials from the WEN Research Group. EAR 419 and EAR 400 are archived course materials shared for public reference. Enrolled students should use the syllabus provided for their current term.
Courses
EAR 419 — Environmental Aqueous Geochemistry
Study the chemical composition of surface water and groundwater through geochemical calculations, water-sample analysis, and scientific interpretation.
Archived teaching materials — Fall 2024
EAR 400 — Machine Learning in Earth and Environmental Sciences
Use R to organize and visualize environmental data, perform geospatial analysis, and apply machine learning in a project using real data.
Archived teaching materials — Spring 2025
Data Science in Earth and Environmental Sciences
Learn R and Python through activities that connect an Earth or environmental science question with a data-analysis workflow and interpretation.
Short learning modules
AI’s Water Footprint: What the Evidence Can and Cannot Tell Us
Module 7 of Syracuse University’s AI Literacy Skills Microcredential, co-designed by Tao Wen and Syracuse colleagues. Wen’s module uses peer-reviewed research and a Central New York case study to examine AI’s water use and evaluate environmental claims.
Can River Chemistry Reveal Catchment Lithology?
Compare linear and neural-network classifiers using river chemistry in this PyTorch module by Tao Wen for IAMG 2026.