Jeongho Park

Papers

Total Citations

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About

Jeongho Park is a rising star in embodied AI and autonomous navigation, whose work bridges the gap between robotic efficiency and human-centered interaction. His primary research areas include socially-aware navigation, object goal navigation, and commonsense reasoning for robotics. Park’s most impactful contribution is **SCAN**, a socially-aware navigation framework that uses Monte Carlo Tree Search to enable robots to move through crowded spaces without causing discomfort to pedestrians—a critical step toward real-world deployment in malls, hospitals, and airports. His follow-up work, **OVG-Nav**, tackles object goal navigation by introducing a Commonsense-Aware Object Value Graph, allowing robots to infer which objects are most likely near a target (e.g., finding a cup near a coffee machine) in unseen environments. With over 16 citations across his top papers since 2023, Park’s research is already influencing the next generation of navigation systems. His work stands out for integrating common-sense priors into visual navigation, moving beyond pure geometry to semantic understanding. As a researcher, Park exemplifies how combining reinforcement learning with human-aware reasoning can create robots that are not just functional, but truly collaborative.