Byron Boots is an American roboticist and academic. He is the Amazon Professor of Machine Learning at the University of Washington (UW). Boots is also the co-founder and chief executive officer of Overland AI, a technology startup.
Byron Boots | |
|---|---|
| Nationality | United States |
| Alma mater | Carnegie Mellon University |
| Scientific career | |
| Fields | Robotics |
| Doctoral advisor | Geoffrey J. Gordon |
Career
editBoots received his Ph.D. from the School of Computer Science at Carnegie Mellon University under the advisory of Geoffrey J. Gordon.[1][2] He later became an assistant professor at the Georgia Institute of Technology.[3]
He is currently the Amazon Professor of Machine Learning at the University of Washington.[4]
In 2022, Boots co-founded the technology startup Overland AI to develop off-road autonomous vehicles.[5] In 2024, the U.S. Army and the Defense Innovation Unit (DIU) jointly awarded the startup a $18.6 million contract to develop autonomy software for the Army's Robotic Combat Vehicle (RCV) program.[6]
Boots has received several awards for his work on robotics, machine learning, and artificial intelligence. They include the NSF CAREER award in 2018,[7] the Robotics: Science and Systems (RSS) Early Career Award in 2020,[8] and the DARPA Young Faculty Award in 2022.[9]
References
edit- ^ "Robotics | Computer Science & Engineering". robotics.cs.washington.edu.
- ^ https://www.cs.cmu.edu/~ggordon/
- ^ "Byron Boots | School of Interactive Computing". ic.gatech.edu.
- ^ "The Amazon Professorships in Machine Learning | Paul G. Allen School of Computer Science & Engineering". www.cs.washington.edu.
- ^ "Secretive new startup focuses on off-road autonomous vehicles, led by UW robotics experts – GeekWire".
- ^ "UW spinout Overland AI raises $10M for off-road self-driving tech used by U.S. military – GeekWire".
- ^ "CAREER Award To Help IC's Byron Boots Bridge Gap Between Machine Learning, Engineering | Research". research.gatech.edu.
- ^ "Byron Boots earns RSS Early Career Award for contributions to robot learning".
- ^ https://www.darpa.mil/attachments/YFAAwardees2022.pdf