Thomas Gebhart

I am a computer scientist, applied mathematician, and 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 am particularly interested in systems where knowledge is parameterized or transformed by networks, as is the case with deep learning, knowledge graphs, and numerous settings within the computational social sciences. Modeling these network-structured knowledge domains with the proper level of mathematical abstraction allows for better control and more efficient usage of the domain’s accumulated knowledge, resulting in, for example, more faithful representations of embedded information, more explainable AI, and better insight into the drivers of scientific and technological change.

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.