Thomas Gebhart

I am a computer scientist, applied mathematician, and machine learning research scientist at the University of Minnesota. My research is focused on the application of ideas from machine learning, network science, and algebraic topology to a range of multi-disciplinary problems. My work is broadly motivated by a desire to understand how knowledge is acquired, structured, and employed by machines, humans, or their larger collective structures. I study how digital technologies—particularly artificial intelligence—shape and are shaped by the production of knowledge, and I build the information infrastructure required to manage that change. My research pairs representation learning, network science, and statistical theory with terabyte-scale data—such as hundreds of millions of papers, patents, and grants—to improve the performance, auditability, and interpretability of machine learning models applied within social and organizational contexts.

I received a Ph.D. in Computer Science from the University of Minnesota in 2023. I also hold B.S. degrees in Mathematics and Economics from the University of Minnesota.

My CV is available here.