Daniel Huang

I am the founder of Base26 Labs where we explore the convergence of language, data, and executable code. Our current focus is PLT (Programming Language Theory) for Software 3.0—formal abstractions for systems that blend neural and symbolic computation.

Previously, I was an assistant professor of computer science at San Francisco State University (SFSU). I completed my PhD at Harvard, advised by Professor Greg Morrisett, and have been fortunate to collaborate with mentors like Professor Dawn Song (UC Berkeley) and Jean-Baptiste Tristan (AWS). My academic research spanned AI, programming languages/formal methods, and quantum computing.