Dr. Tyler Cody
Tyler received a B.S. in Systems Engineering from the University of Virginia (UVa) in spring 2018, and, as part of an early research program, transitioned into UVa's Systems Engineering doctoral program in fall 2018. He currently studies systems theory, machine learning, and probability under Professor Peter Beling. Tyler's research seeks to connect the foundations of systems theory and learning theory, in an effort to contribute to the broader research community's interest in developing a principled discipline of AI systems engineering. His doctoral work is scoped to investigate relationships between systems design, transfer learning, and generalization, as they relate to system life-cycles. Tyler has worked in applied machine learning, including areas such as rotorcraft, satellite communications, and industrial machinery, in experiences stemming from undergraduate research at UVa and NASA Glenn Research Center.
Advisor: Dr. Peter Beling
Dissertation Area: A Systems Theoretic Approach to the Design of Systems with Learning Algorithms
Anticipated Graduation Year: 2021
Selected Publications:
Tyler Cody, Stephen Adams, Peter A. Beling. “A Systems Theoretic Perspective on Transfer Learning.” IEEE SysCon 2019.
Tyler Cody, et. al. “Transferring Random Samples in Actuator Systems for Binary Damage Detection.” IEEE PHM 2019.
Lead Author
- Presentation - AI4SE 2021: "Bringing Reliability, Prognostics, and Testing to Machine Learning"
- Presentation - Enabling SE for AI with Test and Evaluation Harnesses for Learning Systems
- Presentation - AI4SE 2023 Panel: Certification of Learning-Based Systems - OT&E Takeaways on Credentialing Machine Learning (Cody)