Papers
6
Total Citations
173
H-Index
6
About
Jaehyun Yoo is a leading researcher at the intersection of robotics, machine learning, and wireless sensor networks, whose work has garnered over 170 citations. His primary research areas include multi-robot systems, active sensing, and semi-supervised learning for localization and control. Yoo’s most influential contribution is his 2020 paper on multi-robot active sensing with distributed Gaussian processes (77 citations), which pioneered methods for multiple robots to collaboratively explore unknown environments and converge on global maxima using noisy sensor data—a breakthrough for autonomous exploration. He has also made seminal advances in target localization, notably introducing online semi-supervised support vector regression (42 citations) that dramatically reduces the need for costly labeled training data while maintaining high accuracy in wireless sensor networks. His innovative work extends to mobile robot localization using wireless signal strengths and event-triggered model predictive control that compensates for model uncertainties through machine learning. Yoo’s consistent focus on semi-supervised learning—spanning Laplacian SVR and least square SVR—has established him as a key figure in making autonomous systems more data-efficient and adaptive, with applications ranging from environmental monitoring to industrial automation.
Research Focus
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Top Papers
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- 6Online estimation using semi-supervised least square SVR9 citations · 2014