Dan Fu
CS PhD at Stanford. Studying the Intersection of Systems and Machine Learning.
About Me
I'm on the academic job market this year!
I'm a final-year Computer Science PhD candidate at Stanford, where I'm co-advised by Chris Ré and Kayvon Fatahalian, affiliated with the Stanford AI Lab, Stanford CRFM, the Stanford Machine Learning Group, DAWN, and the Stanford Computer Graphics Lab. I'm also an academic partner with Together AI.
In my research, I develop more efficient algorithms for ML, with a focus on developing solutions that are both theoretically efficient and practically effective. Recently, I've been working on efficient ML architectures that scale sub-quadratically in sequence length and model dimension, and hardware-aware systems algorithms to translate these theoretical gains to practical savings. I'm also excited to apply these algorithms to new scientific and medical applications.
I started the Stanford MLSys Seminar Series in Fall 2020, and I'm excited to see it grow to more than 16,000+ subscribers since then, with 30,000+ monthly views. Check us out on YouTube!