Hongqiu Wang
Papers
3
Total Citations
76
H-Index
3
About
Hongqiu Wang is a rising researcher at the forefront of AI-driven robotic surgery, specializing in surgical scene understanding, visual reasoning, and human-machine interaction. His work bridges computer vision and natural language processing to enhance cognitive assistance in the operating room. Wang’s most cited paper, “Video-Instrument Synergistic Network for Referring Video Instrument Segmentation in Robotic Surgery” (2024, 50 citations), introduces a novel framework that enables precise, query-specific segmentation of surgical instruments—a critical step toward context-aware robotic assistance. He further advances surgical documentation with “Dynamic Interactive Relation Capturing via Scene Graph Learning for Robotic Surgical Report Generation” (2023, 20 citations), which models complex instrument-tissue interactions to automate report creation. Most recently, his work “Enhancing Visual Reasoning With LLM-Powered Knowledge Graphs for Visual Question Localized-Answering in Robotic Surgery” (2025, 6 citations) integrates large language models with structured knowledge to answer surgical queries with spatial precision, reducing expert workload. Wang’s contributions are shaping the next generation of intelligent surgical systems, making robotic surgery safer, more transparent, and more accessible for training and real-time decision support.
Research Focus
Key Achievements
Top Papers
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