Luke Bhan
- Program Year: 2
- Academic Institution: University of California, San Diego
- Field of Study: Intelligent Systems, Robotics and Control
- Academic Advisor: Yuanyuan Shi
- Practicum(s):
Lawrence Berkeley National Laboratory (2024) - Degree(s):
M.S. Computer Science, Vanderbilt University, 2022; B.S. Physics and Computer Science, Vanderbilt University, 2022 - Personal URL: https://lukebhan.com/
Summary of Research
Luke is currently studying the application and design of learning algorithms (Neural Operators, Reinforcement Learning, NeuralODEs) for control of dynamical systems. His work is applicable to many engineering problems such as temperature regulation in buildings, power plant design, and robotic manipulators. Previously, Luke worked in computational plasmonics designing simulations for atom ionization under strong lasers.Publications
Journal Papers:[J8] Maxence Lamarque, Luke Bhan, Yuanyuan Shi, Miroslav Krstic. Adaptive Neural-Operator Backstepping Control of a Benchmark Hyperbolic PDE. To appear, Automatica.
[J7] Maxence Lamarque, Luke Bhan, Rafael Vazquez, Miroslav Krstic. Gain
Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation. To appear, IEEE Transactions on Automatic Control.
[J6] Luke Bhan, Yuanyuan Shi, Miroslav Krstic. Adaptive control of reac-
tion diffusion PDEs via neural operator-approximated gain kernels. System
& Control Letters, Volume 195. 2024.
[J5] Miroslav Krstic, Luke Bhan, Yuanyuan Shi. Neural operators of backstepping controller and observer gain functions for reaction diffusion PDEs. Automatica, Volume 164. 2024.
[J4] Luke Bhan, Yuanyuan Shi, Miroslav Krstic. Neural operators for bypassing gain and control computations in PDE backstepping. IEEE Transactions on Automatic Control, Volume 69. 2023.
[J3] Luke Bhan, Cody L Covington, Kalman Varga. Laser-Driven Petahertz Electron Ratchet Nanobubbles. Nano Letters, Volume 22. 2022.
[J2] Luke Bhan, Cody L Covington, Kalman Varga. Signatures of atomic
structure in subfemtosecond laser-driven electron dynamics in nanogaps. Physical Review B, Volume 105. 2022.
[J1] Luke Bhan, Cody L Covington, Jason Rivas, Kalman Varga. Simulation of photo-electron spectrum and electron scattering by dual time
propagation. The Journal of Chemical Physics, Volume 154. 2021.
Conference Publications:
[C10] Luke Bhan*, Peijia Qin*, Miroslav Krstic, Yuanyuan Shi. Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems. In Proceedings of Learning for Dynamics and Control (L4DC), 2025.
[C9] Sharath Matada, Luke Bhan*, Yuanyuan Shi, Nikolay Atanasov. Generalizable Motion Planning via Operator Learning. In Proceedings of International Conference on Learning Representations (ICLR), 2025.
[C8] Luke Bhan*, Yuexin Bian*, Miroslav Krstic, Yuanyuan Shi. PDE
Control Gym: A Benchmark for Data-Driven Boundary Control of Partial
Differential Equations. In Proceedings of Learning for Dynamics and Control (L4DC), 2024.
[C7] Luke Bhan, Yuanyuan Shi, Iasson Karafyllis, Miroslav Krstic, James B
Rawlings. Moving-Horizon Estimators for Hyperbolic and Parabolic PDEs
in 1-D. In Proceedings of American Control Conference (ACC), 2024.
[C6] Luke Bhan, Yuanyaun Shi, Miroslav Krstic. Neural Operators for
Hyperbolic PDE Backstepping Feedback Laws. In Proceedings of IEEE
Conference on Decision and Control (CDC), 2023.
[C5] Luke Bhan, Yuanyaun Shi, Miroslav Krstic. Neural Operators for Hy-
perbolic PDE Backstepping Kernels. In Proceedings of IEEE Conference
on Decision and Control (CDC), 2023.
[C4] Luke Bhan, Yuanyaun Shi, Miroslav Krstic. Operator learning for
nonlinear adaptive control. In Proceedings of Learning for Dynamics and
Control (L4DC), 2023.
[C3] Luke Bhan, Marcos Quinones-Grueiro, Gautam Biswas. Concurrent
policy blending and system identification for generalized assistive control.
In Proceedings of International Conference on Robotics and Automation
(ICRA), 2022.
[C2] Luke Bhan, Marcos Quinones-Grueiro, Gautam Biswas. Fault toler-
ant control combining reinforcement learning and model-based control. In
Proceedings of International Conference on Control and Fault-Tolerant Sys-
tems (SysTol), 2021.
[C1] Adam Stager, Luke Bhan, Andreas Malikopoulos, Liuhui Zhao. A
Scaled Smart City for Experimental Validation of Connected and Automated
Vehicles. In Proceedings of IFAC Symposium on Control in Transportation
Systems (CTS), 2018.
Awards
Underwood Memorial Award for Most Outstanding Senior. Vanderbilt Department of Physics and Astronomy. May 2022.Best Undergraduate Publication. For Simulation of photo-electron spectrum and electron scattering by dual time propagation. Vanderbilt Department of Physics and Astronomy. May 2021.