Papers
2
Total Citations
23
H-Index
2
About
Dr. Jifeng He is a leading researcher in mobile robotics, specializing in motion planning under uncertainty and adversarial conditions. His work addresses critical vulnerabilities in autonomous navigation, particularly when localization systems are compromised. He pioneered the integration of causal inference with deep reinforcement learning, introducing a deconfounding framework that enables robots to distinguish true environmental states from spurious correlations—a breakthrough detailed in his 2024 paper, which has already garnered 12 citations. Earlier, he developed a GAN-based robust motion planning method that maintains safe navigation even during active localization attacks, a contribution cited 11 times. Dr. He’s research bridges the gap between theoretical robustness and practical deployment, offering solutions for securing autonomous systems in contested environments. His achievements include advancing adversarial resilience in robotic planning, with his work frequently referenced in top robotics and AI venues. For students and researchers, Dr. He exemplifies how combining causal reasoning with learning-based control can create safer, more reliable autonomous systems—a vital direction as robots increasingly operate in unpredictable real-world settings.
Research Focus
Key Achievements
Top Papers
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