Phuong D. H. Nguyen
Papers
11
Total Citations
300
H-Index
8
About
Phuong D. H. Nguyen is a robotics and cognitive systems researcher whose work sits at the intersection of reinforcement learning, cognitive architectures, and human-robot interaction. His research focuses on equipping robots with biologically inspired learning mechanisms, enabling them to autonomously acquire, represent, and act upon knowledge of themselves and their environment. Nguyen's most influential contribution, "Intelligent Problem-Solving as Integrated Hierarchical Reinforcement Learning" (2022, 84 citations), advances the understanding of how hierarchical learning principles drawn from cognitive psychology can be embedded in robotic systems. His earlier landmark work on the DAC-h3 cognitive architecture (2017, 74 citations) demonstrated how humanoid robots like the iCub can engage in proactive, mixed-initiative interactions with humans, grounded in neuroscientific theories of the brain. Bridging symbolic planning with learning-based control, his 2019 paper on causal problem-solving (32 citations) addresses a fundamental challenge in autonomous robotics. Across his body of work, Nguyen consistently emphasizes safety-aware, embodied intelligence — from peripersonal space representations for collision avoidance to sensorimotor self-modeling. With over 250 cumulative citations, his research meaningfully advances the goal of robots that learn and interact naturally alongside humans.
Research Focus
Key Achievements
Top Papers
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- 4Compact Real-time Avoidance on a Humanoid Robot for Human-robot Interaction28 citations · 2018
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- 10Hierarchical principles of embodied reinforcement learning: A review5 citations · 2020