Woo-Jeong Baek

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About

Woo-Jeong Baek is an emerging robotics researcher whose work sits at the intersection of uncertainty quantification, safety-critical systems, and human-robot collaboration. Their research addresses one of the most pressing challenges in modern robotics: ensuring that autonomous systems can reliably assess and communicate their own uncertainty, particularly in environments where humans and robots work in close proximity. Baek's most influential contribution, "Uncertainty Estimation for Safe Human-Robot Collaboration Using Conservation Measures" (2023, 7 citations), introduces novel methods for quantifying propagated uncertainty in real time, helping robot systems distinguish genuinely dangerous situations from safe ones — a critical capability for preventing accidents in collaborative workspaces. Complementary work on safety evaluation frameworks further develops online, data-driven approaches to runtime safety compliance monitoring. Beyond safety, Baek has applied probabilistic reasoning to robotic grasping, demonstrating that treating performance metrics statistically and optimizing through sensitivity analysis can meaningfully improve grasp success rates for unknown objects in cluttered environments. Though early in their career, Baek's focused research agenda — making robots not just capable, but demonstrably and quantifiably safe — positions them as a noteworthy contributor to the growing field of trustworthy autonomous systems.