Papers
9
Total Citations
76
H-Index
5
About
Juyoun Park is a pioneering researcher at the intersection of artificial intelligence, robotics, and medical technology, whose work is reshaping how machines perceive and interact with complex environments. Her primary research areas include surgical robotics, human-robot interaction (HRI), and autonomous systems, with a focus on real-time perception, memory modeling, and formal verification. Park’s most impactful contribution is the development of an online robotic tool detection system that enables recognition and prediction of surgical actions, a breakthrough that has garnered 18 citations and promises to enhance precision in robotic surgery. She also introduced the Online Incremental Classification Resonance Network, a novel neural architecture for adaptive HRI that learns from dynamic environments (16 citations). Her recent work on in-sensor multilevel image adjustment using synaptic phototransistors (13 citations) pushes the boundaries of energy-efficient robotic vision, while her formal verification methods for HRI in medical settings (11 citations) ensure algorithmic safety and reliability. Park’s integrated adaptive resonance theory model for episodic and task memory (6 citations) further demonstrates her ability to blend cognitive science with robotics. With over 70 total citations and a growing portfolio of high-impact publications, Park is a rising star whose innovations are driving safer, smarter, and more autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 4Formal Verification for Human-Robot Interaction in Medical Environments11 citations · 2021
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