Dinh Tuan Tran
Papers
11
Total Citations
49
H-Index
5
About
Dinh Tuan Tran is a robotics and human-robot interaction researcher whose work spans affective computing, wearable robotics, autonomous systems, and environmental monitoring. His research is particularly distinguished by its focus on making robots more human-like and socially intelligent — a challenge he addresses through innovative applications of facial expression synthesis, motion learning, and behavioral recognition. Among his most notable contributions, Tran has pioneered approaches to dyadic reaction generation, developing facial tokenization techniques using finite scalar quantization to enable robots to respond naturally in conversational settings. His work on 3D facial pain expression for care training robots demonstrates a meaningful commitment to eldercare applications, where emotionally responsive machines can meaningfully improve caregiver education. His investigations into wearable robot arm configurations further reflect a practical concern for user-centered design and ergonomic integration. Beyond social robotics, Tran has contributed to drone-based night security systems, aquatic environmental monitoring, and deep reinforcement learning for autonomous robot navigation. His growing body of work, accumulating over 45 citations, reflects both breadth and depth across robotics subdisciplines. With several publications appearing as recently as 2025, Tran represents an emerging voice in intelligent systems research with strong potential for continued impact.
Research Focus
Key Achievements
Top Papers
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- 4Investigation of the Mounting Position of a Wearable Robot Arm7 citations · 2022
- 5Approaching Collaborative Manipulation by Pushing-Grasping Fusion5 citations · 2025
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- 8Considerations of Mounting Method for Wearable Robot Arm2 citations · 2022
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- 10Human State Recognition Method in Intelligent Space2 citations · 2023