معرفی
Kevin Angstadt is an Assistant Professor of Computer Science at St. Lawrence University, part of the Department of Mathematics, Computer Science, and Statistics. He holds a Ph.D. from the University of Michigan (2020) and an MCS from the University of Virginia (2016), with undergraduate degrees in Computer Science, Mathematics, and German Studies from St. Lawrence University (2014). His research focuses on the intersection of computer architecture, programming languages, and software engineering, with an emphasis on optimizing programming support for emerging hardware technologies like accelerators and autonomous systems.
Education:
- Ph.D. in Computer Science and Engineering, University of Michigan (2020)
- M.S. in Computer Science, University of Virginia (2016)
- B.S. in Computer Science, Mathematics, and German Studies, St. Lawrence University (2014)
Research Interests: His work spans programming abstractions for hardware accelerators, fault-tolerant autonomous systems, and tools like MNRL and MNCaRT for automata processing. He also collaborates on projects such as StatKey, a statistical simulation tool used by over one million users.
Recent Articles Trends: His publications emphasize hardware-software co-design, resilience in autonomous systems, and debugging support for pattern-matching languages. Recent work includes NSF-funded research on program repair and optimization, and frameworks like LOGI and START for secure autonomous vehicle operation.
Awards:
- NSF Medium Grant ($1.2M, 2022)
- UVA Teaching and Service Award (2017)
- Jefferson Scholars Foundation Fellow (2014–2017)
- Best in Session Award at TECHCON 2016
Advising & Grants: He leads a $1.2M NSF grant and has advised projects on pattern-matching accelerators, autonomous vehicle resilience, and compiler optimization. Collaborates with industry and academic partners on mission-critical systems and software reliability.
Labs/Teams: Core contributor to MNRL (automata processing ecosystem), StatKey (statistical tools), and the START project for resilient autonomous systems. Active in open-source development and hardware-accelerator research groups.
