I lead the Language-Based AI Lab at SFSU. Our aim is 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 programs shift from being comprised largely of code to being increasingly comprised of data, we will need new techniques to reason and build such programs.

We study 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]).

Current

Johnny Gale, Computer Science.

Sanket Shah, Computer Science.

Kai Yee, Mathematics.

Alumni

Chris Camano, Mathematics and Computer Science (now at Caltech).

Sunny Tan, Computer Science (now at SFSU).

Bryce Goldman, Mathematics and Computer Science (now at Stanford).

Pranjal Prafull Newalkar, Computer Science (now at ADP).

Jonathan Tsegaye, Computer Science (now at TechInSF).

Kai Chieh Lo, Computer Science.

Qin Geng, Computer Science.

Darshil Dhameliya, Computer Science.