Summary
Yao-Yi Chiang is a Professor of Computer Science & Engineering at the University of Minnesota with 12 years of professional experience building machine learning methods for spatial artificial intelligence. He develops models that fuse sparse, uneven, multi-modal environmental data across varying spatiotemporal scales to understand complex environmental processes and human–environment interactions. His research is backed by diverse funding from NSF, NIH, DARPA, IARPA, NGA, NEH and industry partners, and he has translated research into practice as chief scientist at AirMap and a visiting researcher at Google AI. He also consults in industry (Meta) and contributes to systems-focused open-source projects, with backend bug fixes and robustness improvements in notable repositories such as toybox and Android platform tooling. Based in the Los Angeles area, he combines deep academic rigor (PhD, USC) with pragmatic engineering experience in runtime systems and drone safety. An interesting facet of his profile is the blend of low-level systems contributions and high-level spatial ML research, reflecting fluency from vtable/elf debugging to geospatial model design.
12 years of coding experience
18 years of employment as a software developer
Ph.D., Ph.D. at University of Southern California
BBA, BBA at National Taiwan University
English, Chinese, Mandarin