DongYang Gao

Nanjing University of Science and Technology

Papers

Total Citations

H-Index

About

DongYang Gao is a rising researcher at the intersection of artificial intelligence, cybersecurity, and embodied systems. His work primarily focuses on safeguarding AI-driven agents against adversarial threats, particularly perception attacks that exploit vulnerabilities in sensory inputs. Gao’s most cited paper, "A new deepfake detection model for responding to perception attacks in embodied artificial intelligence" (2024, 10 citations), introduces a novel framework designed to identify and mitigate deepfake-based manipulations in real-time, ensuring the reliability of autonomous systems operating in dynamic environments. This contribution is critical as embodied AI—from drones to humanoid robots—becomes increasingly integrated into daily life. By combining adversarial robustness with detection algorithms, Gao addresses a pressing need for trustworthiness in AI perception. Though early in his career, his work signals a strong commitment to bridging theoretical security models with practical deployment challenges. His research not only advances the field of AI safety but also provides foundational tools for future studies on resilient autonomous agents. Gao’s growing citation count reflects the timely relevance of his contributions, positioning him as a promising voice in the fight against emerging AI-driven threats.