Daniel Huang

I am the founder of Base26 Labs where we explore the convergence of language, data, and executable code. Our current focus is the development of neuro-symbolic AI, spanning the spectrum from neural perception to symbolic reasoning, to apply digital intelligence to solve problems in the physical world.

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.