Michael Lu
Papers
2
Total Citations
9
H-Index
2
About
Michael Lu is a researcher at the forefront of real-time safety verification for autonomous systems. His primary focus lies in Hamilton-Jacobi (HJ) reachability analysis, a powerful but computationally intensive technique for formally verifying the safety of nonlinear systems under disturbances. Lu’s major contribution is pioneering the use of Field-Programmable Gate Arrays (FPGAs) to overcome the "curse of dimensionality" that has historically limited HJ reachability to offline or low-dimensional applications. His most cited work, "Real-Time Hamilton-Jacobi Reachability Analysis of Autonomous System With An FPGA" (2021, 7 citations), demonstrates a hardware-accelerated approach that enables real-time safety checks for complex autonomous vehicles. A follow-up paper (2020, 2 citations) further refines this FPGA-based formal verification framework. By translating a traditionally software-bound algorithm into parallel hardware logic, Lu has opened the door for provably safe autonomous operation in dynamic environments—a critical step toward deploying self-driving cars, drones, and robotics in the real world. His work bridges the gap between theoretical formal methods and practical embedded systems, making him a key innovator in safety-critical autonomy.
Research Focus
Key Achievements
Top Papers
- 1
- 2Real-Time Formal Verification of Autonomous Systems With An FPGA2 citations · 2020