Papers
5
Total Citations
25
H-Index
2
About
Jaeyoon Jang is a leading researcher at the intersection of human-robot interaction (HRI), computer vision, and assistive technology for the elderly. His work focuses on enabling robots to perceive and interact with humans more naturally, with key contributions in robust age and gender estimation, facial landmark localization, and multi-modal identity recognition. Jang’s pioneering 2017 paper on “Robust Deep Age Estimation Method Using Artificially Generated Image Set” (12 citations) introduced innovative data augmentation techniques to overcome the limitations of small-scale datasets in deep learning, a foundational challenge for real-world HRI systems. He further advanced the field with a convergence system for identity, gender, and age recognition tailored to resource-constrained robot environments, and developed a position regression network for precise facial landmark localization, particularly around the eyes—critical for gauging human interest and attention. In his highly relevant 2024 study (7 citations), Jang evaluated human-care robot services for the elderly, addressing the urgent social issue of loneliness and depression exacerbated by the pandemic. His work not only pushes the boundaries of technical robustness but also directly contributes to socially impactful applications, making him a notable figure in socially assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1Robust Deep Age Estimation Method Using Artificially Generated Image Set12 citations · 2017
- 2
- 3Multi-pose Face Registration Method for Social Robot2 citations · 2018
- 4
- 5