John Alora
External Research Affiliate
John was a graduate student in the Department of Aeronautics and Astronautics at Stanford University. He completed his B.S. degree in electrical engineering at the United States Air Force Academy (USAFA) in 2014 and subsequently, his M.S. degree in Aeronautics and Astronautics at MIT in 2016 under the supervision of Professor Sertac Karaman. He was also a Draper Fellow at Draper Labs working on implementing task and motion planning algorithms for UAVs operating in contested environments. He is currently supported by the Secretary of the Air Force STEM PhD Fellowship.
John's research interests lie at the intersection of robotics, control theory, and optimization. His current work involves development of novel physics-based machine learning techniques for control of infinite-dimensional systems, with applications to soft robots and autonomous aircraft.
John is an Air Force pilot with over 1,000 flight hours; prior to Stanford, he flew the B-52H and deployed across the globe in support of the President's strategic objectives.
Awards:
- Secretary of the Air Force STEM Fellowship (2021)
- Draper Fellowship (2014-2016)
- Distinguished Graduate (Top 10%), USAFA
Publications
9 publications · full lab bibliography
- H. Buurmeijer, L. Pabon, J. Alora, R. Kaudinya, G. Haller, and M. Pavone, “Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds,” Proc. IEEE Conf. on Decision and Control, 2025. (In Press)
- J. I. P. Alora, “Learning Dominant Dynamics for Continuum Robot Control,” Ph.D. dissertation, Stanford University, Dept. of Aeronautics and Astronautics, 2025.
- J. Alora, M. Cenedese, G. Haller, and M. Pavone, “Discovering Dominant Dynamics for Nonlinear Continuum Robot Control,” npj Robotics, 2025.
- M. Bazzi, A. Shahid, C. Agia, J. Alora, M. Forgione, D. Piga, F. Braghin, M. Pavone, and L. Roveda, “RoboMorph: In-Context Meta-Learning for Robot Dynamics Modeling,” Proc. of the IFAC/AAAI Int. Conf. on Informatics in Control, Automation and Robotics, 2024.
- L. Pabon, J. Köhler, J. Alora, P. Eberhard, A. Carron, M. Zeilinger, and M. Pavone, “Perfecting Periodic Trajectory Tracking: Model Predictive Control with a Periodic Observer,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2024.
- J. Alora, M. Cenedese, E. Schmerling, G. Haller, and M. Pavone, “Practical Deployment of Spectral Submanifold Reduction for Optimal Control of High-Dimensional Systems,” IFAC World Congress, 2023.
- J. Alora, M. Cenedese, E. Schmerling, G. Haller, and M. Pavone, “Data-Driven Spectral Submanifold Reduction for Nonlinear Optimal Control of High-Dimensional Robots,” Proc. IEEE Conf. on Robotics and Automation, 2023.
- J. Alora, L. Pabon, J. Köhler, M. Cenedese, E. Schmerling, Z. M. N., G. Haller, and M. Pavone, “Robust Nonlinear Reduced-Order Model Predictive Control,” Proc. IEEE Conf. on Decision and Control, 2023.