Ron Fedkiw
Canon Professor
Stanford Computer Science

Ph.D. Applied Mathematics, UCLA

LEFT PHOTO: circa 2005; RIGHT PHOTO: circa 2017

Computer Science Department
Stanford University
Gates Computer Science Bldg., Room 310
Stanford, CA 94305-9020

CS205L: Continuous Mathematical Methods with an Emphasis on Machine Learning
A survey of numerical approaches to the continuous mathematics used throughout computer science with an emphasis on machine and deep learning. Although motivated from the standpoint of machine learning, the course will focus on the underlying mathematical methods including computational linear algebra and optimization, as well as special topics such as automatic differentiation via backward propagation, momentum methods from ordinary differential equations, CNNs, RNNs, etc. Written homework assignments and (straightforward) quizzes focus on various concepts. (Replaces CS205A, and satisfies all similar requirements.) Prerequisites: Math 51; Math 104 or 113 or equivalent or comfort with the associated material.
Slide deck. If you find this useful, please cite BibTeX.
Brief Bio
Fedkiw (the Canon Professor in the School of Engineering) received his Ph.D. in Mathematics from UCLA and spent part of his postdoctoral studies at Caltech in Aeronautics before joining the Stanford Computer Science Department. He was awarded an Academy Award from the Academy of Motion Picture Arts and Sciences (twice: 2008 and 2015), the National Academy of Science Award for Initiatives in Research, a Packard Foundation Fellowship, a Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship, the ACM Siggraph Significant New Researcher Award, an Office of Naval Research Young Investigator Program Award (ONR YIP), the Okawa Foundation Research Grant, the Robert Bosch Faculty Scholarship, the Robert N. Noyce Family Faculty Scholarship, three distinguished teaching awards including the Tau Beta Pi Teaching Excellence Award (for 2020-21), etc. He has published over 140 research papers in computational physics, graphics, learning, and vision, a book on level set methods, and is currently working at the interface between physical simulation and machine learning - having joined the Stanford Artificial Intelligence Laboratory (SAIL) in 2017. Currently, he serves on the editorial board of the Journal of Computational Physics. He was a consultant with Industrial Light + Magic for over 19 years, receiving screen credits on movies such as "Terminator 3: Rise of the Machines", "Star Wars: Episode III - Revenge of the Sith", "Poseidon", "Evan Almighty", "Kong: Skull Island", etc. Currently, he is a consultant at Epic Games (for 4 years). He has graduated 40 Ph.D. students so far, and is very proud of their various amazing accomplishments!



Faces - Simulation/Vision/Learning...

Cloth - Simulation/Vision/Learning...

Trees - Simulation/Vision/Learning...

Computer Vision...

Muscle Simulation & Finite Elements...


Deformable Bodies & Reduced Deformable Bodies...

Rigid Bodies & Articulated Rigid Bodies...

Hair & Fur...

Water, Smoke, & Fire...

Computational Physics...


Ph.D. Students

Former Ph.D. Students Former Postdoctoral Scholars

A Note on Rejected Papers
All too often young researchers get discouraged when they receive peer reviews that are incorrect, misinformed, or all too often merely intended to silence the authors and their ideas. Personally, I have always been amazed that academics who devote their lives to producing new information actually work to censure and diminish the work produced by others, and often take pride in doing just that. As time goes on, one learns to distinguish between those in academia who love the work and those that have instead turned academia into some sort of career aggressively optimizing their stature at the expense of the community as a whole. For young researchers this can be quite daunting, but I strongly encourage you to stick to your ideas and goals and the pursuit of what interests you. Remember, the content of your paper and the value of its ideas are not diminished because it was rejected from your preferred venue. The content of the paper itself does not change because of the name of the journal printed on the upper corner of the page! To emphasize this, I decided to list my 3 most cited REJECTED papers along with their google scholar citation counts:
  • "A Boundary Condition Capturing Method for Multiphase Incompressible Flow", 887 citations, rejected from J. Comp. Phys.
  • "Simulation of Clothing with Folds and Wrinkles", 710 citations, rejected from Siggraph
  • "Fast Surface Reconstruction using the Level Set Method", 590 citations, rejected from Siggraph