Andrej Risteski Announces CMU Course on AI for Scientific Computing
The course covers learned surrogates for PDE solving, forecasting, and sampling.
TLDR
Andrej Risteski, Associate Professor in the Machine Learning Department at CMU, posted that he is teaching 10-749 AI for Scientific Computing in Fall 2026. Each module will include mathematical foundations of classical methods, ML methodology foundations and tricks, and benchmarks plus industry deployment details where public information exists. The syllabus is posted at andrejristeski.github.io/10749F26. Risteski stated he chose the title deliberately to avoid the broader term AI for science, which covers topics such as agentic workflows that the course will not address.
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