Jing-Fen Wang

National Taiwan University, Johns Hopkins University

Papers

Total Citations

H-Index

About

Jing-Fen Wang is a researcher at the intersection of human-robot interaction, assistive robotics, and augmented reality in surgical systems. Her work explores how robots can meaningfully engage with people, whether through personalized social interactions or enhanced spatial awareness in clinical settings. Wang’s most cited paper, “Towards Effective Robot-Assisted Photo Reminiscence: Personalizing Interactions Through Visual Understanding and Inferring” (2021, 10 citations), introduces a novel approach to using robots in therapeutic contexts—enabling them to recognize and respond to personal visual cues during reminiscence therapy for older adults. This contribution bridges computer vision and socially assistive robotics, demonstrating how machines can support emotional well-being through tailored interaction. More recently, Wang has advanced surgical robotics with her 2025 paper on an augmented reality measurement tool for the da Vinci Research Kit (dVRK), which integrates real-time distance sensing into an RViz-based interface to improve surgeons’ spatial awareness during robotic-assisted procedures. Her work reflects a commitment to making robotic systems more intuitive, empathetic, and effective across diverse domains—from elder care to the operating room.