Zeying Gong
Papers
1
Total Citations
2
H-Index
1
About
Zeying Gong is an emerging researcher specializing in robot navigation, human-robot interaction, and socially-aware autonomous systems. Their work sits at the intersection of reinforcement learning and cognitive robotics, with a particular focus on enabling robots to navigate safely and intelligently in dynamic, human-populated environments. A standout contribution is the development of **Falcon**, a reinforcement learning architecture introduced in their 2025 paper *"From Cognition to Precognition: A Future-Aware Framework for Social Navigation."* This work represents a significant conceptual leap in the field — moving robots beyond reactive perception toward anticipatory reasoning, allowing them to predict future human movements rather than simply responding to current states. This predictive, "precognitive" approach addresses one of the most persistent challenges in social robotics: graceful, efficient navigation in crowded real-world spaces. Though early in its citation trajectory with 2 citations, the recency of the work (2025) suggests its impact is still unfolding. Gong's research holds meaningful implications for the future of assistive robotics, autonomous vehicles, and any system requiring safe co-existence with humans in shared spaces.
Research Focus
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Top Papers
- 1