I don’t like having to hunt all over the internet for quality reference material, so I’m saving us all some trouble. Here are my picks for the “best of the best” when it comes to algorithms, DSP, optics, and information theory.
Computer Vision, Astrometry, and Photography
- First Principles of Computer Vision, Dr. Shree Nayar (Columbia):
- Youtube: https://www.youtube.com/@firstprinciplesofcomputerv3258/featured
- Columbia webpage with materials: https://fpcv.cs.columbia.edu/Monographs
- The very deepest of photography and optics (PSFs, OTFs, etc): https://www.strollswithmydog.com/
- Seriously, this site should be turned into a textbook on Optics!
- Tim Hutchison’s Discussion of Signal and Noise (Part of The Astro Imaging Channel): https://www.youtube.com/live/1PUTWfWgD0g?si=N8kXJapoflagWUpg
- Boyce Astro’s Brief Videos on Luminosity, Star Magnitudes, and Separating Double Stars: https://www.youtube.com/watch?v=5uhXe-FSd10
- Dr. Richard Szeliski’s “Computer Vision: Algorithms and Applications, 2nd ed.” (UWash):
- Available free at https://szeliski.org/Book/
- Additional resources can be found at the same link
Signal Processing – Note that most of these topics can also be applied to image processing
- Dr. Steven Brunton’s Lectures (UWash) on Youtube, Specifically:
- Sparsity and Compressed Sensing: https://www.youtube.com/playlist?list=PLMrJAkhIeNNRHP5UA-gIimsXLQyHXxRty
- Wavelets: https://www.youtube.com/watch?v=y7KLbd7n75g
- Uncertainty Principles and The Fourier Transform: https://youtu.be/D1WfID6kk90?si=OEIYaEqze4vN5_vY
- Dr. Nathan Kutz’s Introduction to Signal Processing (UWash): https://youtu.be/kjw6W0SZe04?si=nLxF72lHBRVhDgA3
- Dr. Ingrid Daubechies giving a very accessible lecture on Wavelets (Abel Prize Presentation, also at Duke): https://www.youtube.com/watch?v=tMV61BZCrhk
RF Engineering
- Dr. Dimitrios Peroulis’s Primer Course on RF Systems Design (Purdue): https://youtu.be/ghXEgO6ib34?si=LaANilWd8If5JGIN
- Dr. Robert O’Donnell’s Course on Radar (UNH, Formerly MIT Lincoln Lab): http://radar-course.org/
Optimal Control and Reinforcement Learning
- Dr. Tim Drake’s Underactuated Robotics Course (MIT): https://youtu.be/uyyBT-MHhLE?si=SSuqaHfyrZQmleaD
- Covers everything about dynamics, linear and nonlinear controls, stability, etc.
- Dr. Steve Strogatz’s Nonlinear Dynamics and Chaos Course (Cornell): https://youtu.be/ycJEoqmQvwg?si=PRVRIGuW31PJlIw7
- Dr. Dimitri Bertsekas’s Lectures on Reinforcement Learning (ASU): https://youtu.be/AdxhPj0PDHM?si=jLCzrXdBhwpNrGdG
DevOps, Containers, and General Programming
- TechWorld with Nana covers just about everything in this domain: https://www.youtube.com/@TechWorldwithNana
Computer Science
- Dr. Tim Roughgarden’s (Stanford) Courses on Algorithms: https://timroughgarden.org/videos.html
- Lehman, Leighton, & Meyer’s (MIT) Textbook “Mathematics for Computer Science”
Information Theory
- Dr. David Mackay’s (Cambridge) Course on Information Theory: https://youtu.be/BCiZc0n6COY?si=OlqYrUBKcPiGNljT
- Mackay’s book is available free at: https://www.inference.org.uk/itprnn/book.pdf