Ria Kim

George Washington University

Papers

1

Total Citations

18

H-Index

1

About

Ria Kim is a leading researcher in medical robotics and intelligent human-robot interaction, with a focus on autonomous ultrasound imaging systems. Her most-cited work introduces a semi-autonomous robotic ultrasound platform that integrates tactile sensing, PID control, and convolutional neural networks to guide probe positioning and image acquisition. This system reduces operator dependency while maintaining diagnostic quality, representing a significant step toward accessible, automated medical imaging. With 18 citations on this foundational paper, Kim’s contributions are shaping the future of robot-assisted diagnostics, particularly in resource-limited settings where skilled sonographers are scarce. Her research bridges robotics, machine learning, and clinical practice, demonstrating how AI-driven tactile feedback can enable safer, more consistent examinations. Kim’s work has been recognized for its translational potential, and she continues to advance semi-autonomous systems that augment rather than replace human expertise. For students and researchers, her career exemplifies how interdisciplinary innovation—combining control theory, deep learning, and haptics—can solve real-world healthcare challenges.

Research Focus

Key Achievements

1
H-Index
1
Papers
18
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Robot-Assisted Semi-Autonomous Ultrasound Imaging With Tactile Sensing and Convolutional Neural-Networks
18 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: George Washington University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago