Yate Ge

Tongji University

Papers

4

Total Citations

12

H-Index

2

About

Yate Ge is a pioneering researcher at the intersection of human-robot interaction (HRI) and generative artificial intelligence, with a focus on democratizing robot programming for non-experts. Their work centers on three key areas: end-user robot programming, human-robot communication, and interactive learning frameworks for service robots. Ge’s most influential contribution is the development of **Cocobo** (2024, 5 citations), a system that leverages large language models (LLMs) as the engine for end-user robot programming, enabling everyday users to program service robots through natural language—a breakthrough that addresses the long-standing challenges of expression space and debugging in HRI. Building on this, **GenComUI** (2025, 4 citations) introduces generative visual aids—such as dynamic map annotations and path indicators—to enhance task-oriented communication between humans and robots, further bridging the gap between verbal commands and robotic action. Ge’s earlier work includes co-designing service robot applications using virtual reality (2023) and developing an interactive learning framework for item ownership relationships (2023), which teaches robots social norms like respecting personal property. With a rapidly growing citation record and a clear trajectory toward making robots accessible and intuitive, Ge is shaping the future of human-robot collaboration.

Research Focus

Key Achievements

2
H-Index
4
Papers
12
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Cocobo: Exploring Large Language Models as the Engine for End-User Robot Programming
5 citations · 2024
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Tongji University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago