Postdoctoral Fellow
Adam Thorpe is a postdoctoral fellow at the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin, working with Ufuk Topcu. He received his Ph.D. from the University of New Mexico, where he worked with Meeko Oishi on data-driven control and human-centered autonomy. He also holds a degree in Languages from the University of New Mexico and is a recipient of the 2024 NSF CPS Rising Stars award.
His research asks how learning-based autonomy can adapt when data, conditions, or environments change, particularly for robotics and dynamical systems operating in uncertain and unpredictable settings where data may be sparse and dynamics may shift over time. To address this, he develops algorithms that allow robots to learn and plan within seconds using online data, neural operator learning methods for modeling complex systems like PDEs, and techniques for human-centered autonomy that adapt to individual users rather than assuming a uniform behavioral model. Together, these efforts draw on Hilbert-space representations and integrate computational modeling with learning-based control in robotics and scientific machine learning. Building on these themes, he is also interested in developing deformable world models that capture how robots interact with changing environments, supporting tasks such as locomotion or manipulation in remote settings where adaptation and transfer are key.
Personal site: https://ajthor.github.io
Linkedin: https://www.linkedin.com/in/adam-thorpe-50b92771/
Google Scholar: https://scholar.google.com/citations?user=bApIsIAAAAAJ