Shouling Ji
Papers
2
Total Citations
31
H-Index
2
About
Shouling Ji is a leading researcher in the security and robustness of intelligent systems, with a primary focus on adversarial machine learning, cyber-physical system security, and multi-agent reinforcement learning (MARL). His work exposes critical vulnerabilities in real-world autonomous technologies. In his highly cited 2021 study, *Remote Attacks on Drones Vision Sensors*, Ji empirically demonstrated how vision sensors in drones and automated vehicles can be maliciously manipulated, highlighting severe safety risks in these increasingly popular systems. This work has accumulated over 25 citations, underscoring its foundational impact on the field of sensor security. More recently, in his 2024 paper *SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems*, Ji pioneered the exploration of adversarial attacks in MARL, revealing how malicious policies can disrupt swarm drone control and robotic collaboration. This research, already garnering 6 citations, marks a significant step forward in understanding security threats during MARL deployment. Through these contributions, Shouling Ji has established himself as a critical voice in ensuring the safe and trustworthy deployment of autonomous and multi-agent systems.
Research Focus
Key Achievements
Top Papers
- 1Remote Attacks on Drones Vision Sensors: An Empirical Study25 citations · 2021
- 2