Tennom Chenlinangjia
Papers
2
Total Citations
22
H-Index
2
About
Tennom Chenlinangjia is a pioneering researcher in human-robot interaction (HRI), specializing in online learning and mutual adaptation between humans and machines. Their work addresses a critical gap in robotics: enabling robots to dynamically learn and adapt during real-time interactions with human partners, rather than relying solely on pre-programmed behaviors. Chenlinangjia’s most-cited paper, “Learning to Interact with a Human Partner” (2015, 19 citations), identifies key challenges in applying online learning to HRI, such as the need for safe exploration strategies that avoid disruptive random actions. This foundational work has influenced subsequent research on adaptive robotics, emphasizing the importance of reciprocal learning in collaborative settings. Their earlier study, “Online Learning in Repeated Human-Robot Interactions” (2014, 3 citations), further explores how robots can improve performance over multiple encounters with the same human partner. By highlighting the unsolved problems of mutual adaptation and online learning, Chenlinangjia has shaped the direction of modern HRI, inspiring new approaches to creating robots that learn seamlessly alongside people—a crucial step toward truly intuitive and effective human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Learning to Interact with a Human Partner19 citations · 2015
- 2Online Learning in Repeated Human-Robot Interactions.3 citations · 2014