My courses share one idea: a model is a tool for making a decision, and a tool you don't understand is a liability. Students build methods from first principles before they use packaged software. They test every result against data, and each course ends with a project on a real engineering problem. Generative AI is welcome as a study partner. The reasoning, and the accountability for it, stay with the student.
Saurav Kumar, School of Sustainable Engineering and the Built Environment
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Numerical Methods for Engineers
The computational toolkit behind modern engineering: error analysis, root-finding, linear systems, curve fitting, integration, and ODEs, all implemented in MATLAB.
Next offered: Fall 2026 (in session) · Undergraduate
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Remote Sensing for Water Resources and Civil Engineering
How satellites, aircraft, and drones see the Earth, and how to turn what they see into decisions, from spectral indices to deep learning and geospatial foundation models.
Next offered: Spring 2027 · Graduate
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Advanced Surface Water Quality Modeling
Watershed and water quality modeling for regulatory decisions, from mass-balance boxes to calibrated SWAT and HSPF models, AI, and data assimilation, ending with a TMDL project.
Next offered: Spring 2028 · Graduate