Dr. Cale Crowder is a Senior Member of the Technical Staff in Cognitive and Emerging Computing at Sandia National Laboratories. At Sandia, Cale’s research focuses on applying machine learning and reinforcement learning techniques with many different applications, including:
Simulating how international disinformation campaigns affect nuclear deterrence foreign policy
Investigating how multiple agents can be trained via reinforcement learning to work collaboratively
Characterizing how hierarchies of reinforcement learning agents can achieve effective strategic planning
Developing trustworthy large language models by limiting hallucinations
Prior to joining Sandia National Laboratories in 2021, Cale earned his Ph.D. in the Department of Biomedical Engineering at Case Western Reserve University (CWRU). At CWRU, Cale developed reinforcement learning techniques to automatically learn to control a model of a paralyzed human arm that was actuated using functional electrical stimulation. He also worked extensively on human intracortical brain computer interface clinical trials. This work was supported by a National Science Foundation Graduate Research Fellowship. As an undergraduate, Cale contributed to multiple fields including: cancer drug delivery, gene therapy, bone biology, and brain computer interfaces.
Cale’s primary research interests include: artificial intelligence (AI); artificial general intelligence; reinforcement learning; multi-agent reinforcement learning; modular, hierarchical reinforcement learning; and AI for optimization, design, and discovery.
Education
Ph.D., Biomedical Engineering, Case Western Reserve University Thesis: Reinforcement Learning for Control of a Multi-Input, Multi-Output Model of the Human Arm
2021
B.S., Biomedical Engineering, The University of Akron
