Jesse Parron
Papers
11
Total Citations
52
H-Index
4
About
Jesse Parron is an emerging researcher specializing in human-robot collaboration (HRC), trust modeling, and smart manufacturing systems. His work sits at the intersection of robotics, artificial intelligence, and human factors engineering, with a particular focus on enabling robots to dynamically understand and respond to human partners in real-world environments. Among Parron's most significant contributions is his development of computational trust frameworks for HRC contexts, including a POMDP-based robot-human trust model and multimodal trust databases that leverage physiological biometrics to quantify and reason about human-robot trust — work that has collectively garnered over 20 citations since 2022. His Teaching-Learning-Prediction-Collaboration model represents a meaningful advance in enabling robots to interpret dynamic human intentions beyond simple, repetitive task structures. Parron has also demonstrated versatility across application domains, from designing AI-embedded smart glove systems for intuitive robot interaction to exploring autonomous crop harvesting solutions in smart agriculture. His 2025 work introducing Robo-CSK-Organizer, a commonsense knowledge-enhanced perception system, signals a forward-looking push toward deploying robots in unpredictable, uncontrolled environments. Collectively, his portfolio reflects a dedicated effort to make human-robot partnerships safer, more intuitive, and genuinely collaborative in Industry 5.0 contexts.
Research Focus
Key Achievements
Top Papers
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- 4A POMDP-based Robot-Human Trust Model for Human-Robot Collaboration6 citations · 2022
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- 8Incorporating Commonsense Knowledge to Enhance Robot Perception3 citations · 2025
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- 10MCROS: A Multimodal Collaborative Robot System for Human-Centered Tasks3 citations · 2024