Matthew Gombolay

Biography:

Dr. Matthew Gombolay is an Assistant Professor of Interactive Computing at the Georgia Institute of Technology. He is the Director and Founder of the Cognitive Optimization and Relational (CORE) Robotics Laboratory. He received a B.S. in Mechanical Engineering from the Johns Hopkins University in 2011, an S.M. in Aeronautics and Astronautics from MIT in 2013, and a Ph.D. in Autonomous Systems from MIT in 2017. Gombolay’s research interests span robotics, AI/ML, human-robot interaction, and operations research. Between defending his dissertation and joining the faculty at Georgia Tech, Dr. Gombolay served as technical staff at MIT Lincoln Laboratory, transitioning his research to the U.S. Navy and earning a R&D 100 Award. His publication record includes a best paper award from the American Institute for Aeronautics and Astronautics, best technical paper award from the Conference on Human-Robot Interaction (HRI’22), a finalist for best student paper at the American Controls Conference (ACC’20), and a finalist for best paper at the Conference on Robot Learning (CoRL’20). Dr Gombolay was selected as a DARPA Riser in 2018, received 1st place for the Early Career Award from the National Fire Control Symposium, and was awarded a NASA Early Career Fellowship.

Honors:

Best Technical Advances Paper (HRI’22), March 2022; Best Paper Award (MAIR2 Workshop at ICCV’21), October 2021; Best Paper Award Finalist (CoRL’20), October 2020; Best Student Paper Award Finalist (ACC’20), June 2020; Best AIAA Intelligent Systems Paper, August 2013; Class of 1934 CIOS Honor Roll, Spring 2021, Fall 2020; "Thank a Teacher" Award at Georgia Tech, Fall 2020, Spring 2019, Fall 2018; NASA Early Career Fellowship, September 2019; Early Career Award, National Fire Control Symposium, February, 2018; R&D 100 Award, November 2018; DARPA Riser, 2018; NTSA Modeling & Simulation Team Training Award, December 2015; NSF Graduate Research Fellowship Program Fellow, September 2011. 

Lab/Collaborations:
  • Cognitive Optimization and Relational Robotics Lab (CORE)
Disciplines:
  • Flight Mechanics & Controls
  • Systems Design & Optimization
AE Multidisciplinary Research Areas:
  • Cyberphysical Systems, Safety, and Reliability
  • Large-Scale Computations, Data, and Analytics
  • Robotics, Autonomy, and Human Interactions