General Information
Details
I work to democratize robotic technology – placing the power of robots in the hands of everyone by developing new computational methods (e.g., algorithms, model architectures, etc.) and human factor insights that enable robots to 1) learn novel skills via human demonstration from diverse end-users, 2) understand and support the human in human-robot interaction (HRI) through explainable Artificial Intelligence (xAI), and 3) coordinate human-robot teams, advancing techniques such as Multi-Agent Reinforcement Learning (MARL). I employ human-subjects research methods to inform the formulation of our systems, validate our methods, improve HRI across both subjective and objective metrics, and develop design guidelines for researchers and practitioners alike.
I teach across the areas of robotics, machine learning, and human–robot interaction, emphasizing interactive, human-centered learning and autonomous systems. I have taught courses including:
• CS 3630: Introduction to Perception and Robotics
• CS 4649/7649: Robot Intelligence: Planning
• CS 7648: Interactive Robot Learning
Across all, I engage students in hands-on development of robot frameworks bridging theory and practice.
Selected Honors and Awards
Student Recognition of Excellence in Teaching: 2024 CIOS Award
National Science Foundation (NSF) CAREER Award, February 2024
Best Paper Award (Multi-Agent Interaction and Relational Reasoning [MAIR2] Workshop at the International Conference on Computer Vision [ICCV]), October 2021
Class of 1934 CIOS Honor Roll, Spring ’25, Spring ‘24, Spring ‘23,Spring ‘22, Spring ‘21, Fall ‘20
"Thank a Teacher" Award at Georgia Tech, Fall 2022, Fall 2020, Spring 2019, Fall 2018
NASA Early Career Fellowship, September 2019
Early Career Award, National Fire Control Symposium (NFCS), February, 2018
R&D 100 Award, November 2018
Defense Advanced Research Projects Agency (DARPA) Riser, 2018
NSF Graduate Research Fellowship Program Fellow (GRFP), September 2011
Selected Journal Publications
Scherpereel, K. L., Gombolay, M., Shepherd, M. K., Inan, O. T., Young, A. J. (2024) “Deep Domain Adaptation Eliminates Costly Data Required for Task-Agnostic Wearable Robotic Control.” Science Robotics. [Accepted October 22nd, 2025]
Xue, C., Chen, L., and Gombolay, M. (2025), “Learning Disentangled Rewards from Heterogeneous, Suboptimal Demonstrations.” IEEE Robotics and Automation Letters (RA-L), 10(7), pp. 7047-7054.
Gombolay, G., Silva, A., Schrum, M., Gopalan, N., Hallman-Cooper, J. Dutt, M., and Gombolay, M. (2024) “Effects of Explainable Artificial Intelligence in Neurology Decision Support.” Journal of the American Medical Association.
Tambwekar, P., Silva, A., Gopalan, N., and Gombolay, M. (2023) “Natural Language Specification of Reinforcement Learning Policies through Differentiable Decision Trees.” IEEE Robotics and Automation Letters (RA-L), 8(6), pp. 3621 – 3628.
Zaidi, Z., Martin, D., Belles, N., Zakharov, V., Krishna, A., Lee, K. M., Wagstaff, P., Naik., S., Sklar, M., Choi, S., Kakehi, Y., Patil, R., Mallemadugula, D. Pesce, F., Wilson, P., Wendell, H. Diamond, M. Zhao, B., Moorman, N., Paleja, R. Chen, L., Seraj, E. and Gombolay, M. (2023) “Athletic Mobile Manipulator System for Robotic Wheelchair Tennis.” IEEE RA-L, 8(4), pp. 2245 – 2252.
Silva, A., Moorman, N., William, S., Zulfiqar, Z., Gopalan, N., and Gombolay, M. (2022). “LanCon-Learn: Learning with Language to Enable Generalization in Multi-Task Manipulation Domains.” IEEE RA-L, 7(2), pp. 1635-1642
Seraj, E., Chen, L., and Gombolay, M. (2021). “Coordinating Composite Teams of Heterogeneous Robots for Joint Perception and Control Tasks.” IEEE Transactions on Robotics (T-RO), pp. 1-20.
Wang, Z. and Gombolay, M. (2020). “Learning Scheduling Policies for Multi-Robot Coordination with Graph Attention Networks.” IEEE RA-L, 5(3), pp.4509-4516.
Schrum, M. and Gombolay, M. (2019). “When Your Robot Breaks: Active Learning During Plant Failure.” IEEE RA-L, 5(2), pp.438-445.
Gombolay, M., Yang, X.J., Hayes, B., Seo, N., Liu, Z., Wadhwania, S., Yu, T., Shah, N., Golen, T. and Shah, J., (2018). “Robotic assistance in the coordination of patient care.” International Journal of Robotics Research (IJRR), 37(10), pp.1300-1316.
Gombolay, M., Bair, A., Huang, C., and Shah, J. (2017). "Computational design of mixed-initiative human–robot teaming that considers human factors: situational awareness, workload, and workflow preferences." The International Journal of Robotics Research, 36(5-7), pp. 597-617.
Gombolay, M., Gutierrez, R., Clarke, S., Sturla, G., and Shah, J. (2015). “Decision-Making Authority, Team Efficiency and Human Worker Satisfaction in Mixed Human-Robot Teams.” Autonomous Robots (AuRo), 39(3), pp. 293-312.
Selected Peer-Reviewed Conference Publications
Chen, L. and Gombolay, M. (2025). “ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Interpretable Reward Design in Robotics.” In Proceedings of the International Conference on Machine Learning (ICML).
Alrashedy, K., Tambwekar, P., Zaidi, Z., Langwasser, M., Xu, W., and Gombolay, M. (2025). “Generating CAD Code with Vision-Language Models for 3D Designs.” In Proceedings of the International Conference on Learning Representations (ICLR).
Yang, Y., Chen, L, Zaidi, Z. and Gombolay, M. (2024). “Enhancing Safety in Learning from Demonstration Algorithms via Control Barrier Function Shielding.” In Proc. ACM/IEEE Intl’l Conference on HRI.
*Moorman, N., Gopalan, N., Singh, A., Hedlund, H., and Gombolay, M. (2023) “Investigating the Impact of Experience on a User’s Ability to Perform Hierarchical Abstraction.” In Proceedings Robotics: Science and Systems. [Best Student Paper Nomination]
Lee, K. M., Krishna, A., Zaidi, Z., Paleja, R., Chen, L., Hedlund-Botti, E., Schrum, M., and Gombolay, M. (2023). “The Effect of Robot Skill Level and Communication in Rapid, Proximate Human-Robot Collaboration.” In Proc. ACM/IEEE Int’l Conference HRI.
Schrum, M., Hedlund, E. and Gombolay, M. (2022) “MIND MELD: Personalized Meta-Learning for Robot-Centric Imitation Learning.” In Proc. ACM/IEEE International Conference on HRI. [Best Technical Paper Award]
Paleja, R., Ghuy, M., Arachchige, N., and Gombolay, M. (2021), “The Utility of Explainable AI in Ad Hoc Human-Machine Teaming.” In Proc. Conference on Neural Information Processing Systems (NeurIPS).
Niu, Y., Paleja, R., and Gombolay, M. (2021). “Multi-agent Graph Attention and Communication.” In Proc. AAMAS. [25% Acceptance Rate]
Chen, L., Paleja, R., Gombolay, M. (2020). “Learning from Suboptimal Demonstration via Self-supervised Reward Regression.” In Proc. Conference on Robot Learning. [Best Paper Award Finalist]
Seraj, E. and Gombolay, M. (2020). “Coordinated Control of UAVs for Human-Centered Active Sensing of Wildfires.” In Proceedings of the American Controls Conference (ACC). [Best Student Paper Award Finalist]
Silva, A., Killian, T., Jimenez-Rodriguez, I., Son, S.-H., and Gombolay, M. (2020). “Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning.” In Proc. International Conference on AI and Statistics (AISTATS).
Natarajan, M. and Gombolay, M. (2020). “Effects of Anthropomorphism and Accountability on Trust in Human Robot Interaction.” In Proc. ACM/IEEE Int’l Conference on HRI.