Simon Barke was born in Germany where he studied physics. For a while, he lived in Moshi, Tanzania, and worked at different local schools and universities. Over the last decade, he has had the privilege to be involved in a number of exciting projects. He was a scientific monitor at the LIGO gravitational wave detector in Livingston, Louisiana. He got his PhD for research on low-frequency gravitational wave observatories in space at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Hannover, Germany, with a focus on inter-spacecraft frequency distribution for LISA, the upcoming Laser Interferometer Space Antenna by the European Space Agency. He then moved to the University of Florida where he conducted research at the Department of Physics on the detection mechanism for ALPS, a dark matter generator and detector that is under construction at the German Electron Synchrotron DESY (Hamburg, Germany). Currently Simon works at the Department of Mechanical and Aerospace Engineering on the development of a LISA Charge Management device under NASA contract.
He also tried to climb Mount Kilimanjaro, plays online games, and cannot sing (at all).
Education
Doctor rerum naturalium (physics)
Teaching Interests
Limiting fundamental and technical noise sources for ground and space-based gravitational wave observatories
Research Interests
Ultra-low-frequency noise of custom and COTS devices (electronics, electro-optics, lasers), flight hardware development for space missions, mission concepts for future gravitational wave observatories
Research Interests:
Nonlinear Control, Adaptive Control, AI-Based Control Methods, Multi-Agent Systems
Selected Publications:
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O. Patil, R. Kamalapurkar, and W. Dixon, ”A saturated RISE controller with exponential
stability guarantees,” IEEE Trans. Autom. Control, 2025. -
O. Patil, D. Le, E. Griffis, and W. Dixon, ”Lyapunov-based deep residual neural
network (ResNet) adaptive control,” IEEE Access, 2025. -
O. Patil, R. Sun, S. Bhasin, and W. E. Dixon, ”Adaptive control of time-varying parameter systemswith asymptotic tracking,” IEEE Trans. Autom. Control, vol. 67, no. 9, pp. 4809–4815, 2022.
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O. Patil, D. Le, M. Greene, and W. E. Dixon, ”Lyapunov-derived control and adaptiveupdate laws for inner and outer layer weights of a deep neural network,” IEEE Control Syst Lett., vol. 6,pp. 1855–1860, 2022.
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W. Makumi, O. Patil, and W. Dixon, ”Lyapunov-based adaptive deep learning for
approximate dynamic programming,” Automatica, vol. 180, p. 112462, 2025.
Notable Awards:
Graduate Student Research Award, University of Florida, Department of Mechanical and Aerospace Engineering, 2023
Professional Memberships and Fellowships
American Physical Society, Member