Michelle Zhu
Papers
7
Total Citations
47
H-Index
4
About
Michelle Zhu is a researcher whose work sits at the intersection of robotics education, human-robot collaboration, and intelligent autonomous systems. She has made notable contributions to pedagogical innovation in computing, most prominently through her development of situated learning-based robotics curricula that emphasize hands-on, project-oriented experiences over traditional textbook instruction. Her 2021 paper empowering computing students through situated learning in robotics has garnered 23 citations, reflecting meaningful influence in STEM education circles. Beyond the classroom, Zhu's research extends into cutting-edge human-robot collaboration, including the development of a POMDP-based trust model that enables robots to dynamically assess and respond to human behavior during collaborative tasks. Her work on multimodal collaborative robot systems and vision-speech-based approaches to manufacturing assistance speaks to her commitment to advancing Industry 5.0-ready technologies. She has also championed robotics accessibility across age groups, designing programs that bring hands-on learning to K-12 students. Taken together, Zhu's portfolio reflects a researcher equally invested in building the next generation of robotics practitioners and pushing the technical frontiers of intelligent, human-centered robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Situated Learning-Based Robotics Education6 citations · 2020
- 3A POMDP-based Robot-Human Trust Model for Human-Robot Collaboration6 citations · 2022
- 4
- 5MCROS: A Multimodal Collaborative Robot System for Human-Centered Tasks3 citations · 2024
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- 7