Jjh Lee

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About

Driven by the challenge of autonomous exploration in extreme environments, Dr. Jjh Lee’s research focuses on active perception, robotic navigation, and environmental monitoring, with a particular emphasis on underwater robotics. Lee’s most notable contribution is the development of energy-optimal strategies for localising unknown underwater plume sources using autonomous gliders. In the highly cited 2018 work, “Active perception for plume source localisation with underwater gliders” (12 citations), Lee pioneered a specialised Gaussian process regression technique that enables robots to intelligently infer source locations while minimising energy expenditure—a critical advancement for long-duration, deep-sea missions. This work bridges probabilistic machine learning with field robotics, offering a principled framework for decision-making under uncertainty. By integrating active sensing with resource-constrained platforms, Lee’s research has laid essential groundwork for autonomous environmental sampling, chemical spill response, and marine ecosystem monitoring. The impact of this work is reflected in its adoption by researchers tackling similar source localisation problems in aerial and ground robotics. Lee’s contributions stand out for their rigorous mathematical foundation and practical relevance, marking a significant step toward truly autonomous, energy-aware robotic systems operating in the world’s most inaccessible environments.