While at SFSU, I lead the Language-Based AI Lab. Our aim was to bridge the well-studied world of programming with code, i.e., using a language, with new ways of programming with data, i.e., using AI/ML. As software becomes increasingly data-driven, new techniques are required to build, reason about, and verify these hybrid systems.

We studied uncertainty quantification of deep learning systems (to reason about AI systems, [Push]), function approximation with derivative information (to enable new applications in science, [DCNN]), neuro-symbolic systems (to understand the mixing of code and data), and adiabatic quantum computing (to leverage new hardware, [a2c]).

Alumni

I was fortunate to mentor a fantastic group of students.

  • Kai Yee, Mathematics.
  • Chris Camano, Mathematics and Computer Science (pursuing PhD Caltech, NSF GRFP Fellowship).
  • Sunny Tan, Computer Science (continuing at SFSU).
  • Bryce Goldman, Mathematics and Computer Science (purusing masters at Stanford).
  • Pranjal Prafull Newalkar, Computer Science (Joined ADP after graduation).
  • Jonathan Tsegaye, Computer Science (Joined TechInSF after graduation).
  • Kai Chieh Lo, Computer Science.
  • Qin Geng, Computer Science.
  • Darshil Dhameliya, Computer Science (Joined Democratizing Education after graduation).