Jeff Fessler is a Professor of Electrical Engineering and Computer Science at the University of Michigan with a research and teaching career spanning decades and seven years listed in recent experience metrics. He coauthored a 2024 Cambridge textbook, Linear Algebra for Data Science, Machine Learning, and Signal Processing, reflecting his focus on matrix methods with real-world applications across EECS, biomedical engineering, and radiology. A Stanford PhD and Purdue BS in EE underpin his work at the intersection of imaging, signal processing, and computational methods. He also contributes to major open-source projects as a technical writer for the Julia language, improving documentation and practical examples for a widely used scientific computing community. Known for translating deep theory into usable tools and pedagogy, he combines rigorous scholarship with hands-on contributions that benefit both students and practitioners.
7 years of coding experience
Bachelor of Science - BS, Electrical Engineering, Bachelor of Science - BS, Electrical Engineering at Purdue University
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Stanford University
Contributions:10 commits, 10 PRs, 32 comments in 3 years 11 months
Contributions summary:Jeff primarily focused on improving the documentation within the Julia programming language repository. Their contributions include correcting documentation errors, clarifying the use of functions, and providing examples. They also updated documentation to reflect changes in language features and best practices, such as the preferred use of `show` over `display`. Additionally, they made small corrections in function docstrings.
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Jeff Fessler - Professor at University of Michigan, EECS Department