Queen Mary University of London

🇬🇧 GB

Papers

504

Total Citations

13,508

H-Index

61

Researchers

396

About

Queen Mary University of London stands as a vibrant, multidisciplinary research institution with remarkable breadth across robotics, artificial intelligence, human-robot interaction, and biomedical engineering. With deep roots in both fundamental science and applied innovation, QMUL has established itself as a compelling destination for researchers and students seeking to work at the intersection of cutting-edge technology and real-world impact. The institution's robotics and AI portfolio is impressively diverse. Pioneering work in aerial additive manufacturing with autonomous robot swarms demonstrates QMUL's ambition in pushing the boundaries of what autonomous systems can build and create. Complementing this, their research into soft continuum robots and tactile sensing—including the uSkin sensor integrated on the humanoid iCub—reflects a sophisticated understanding of how robots must physically engage with unstructured environments. Meanwhile, foundational contributions to hand tracking and affective posture recognition have shaped how machines perceive and respond to human behavior, with work on detecting user engagement with robot companions remaining highly influential in social robotics more than a decade after publication. QMUL's human-centered AI research is equally compelling. Their explorations of robotic hand augmentation and neural body representation reveal a deep commitment to understanding how humans and machines can symbiotically coexist, while contributions on AI in medical robotics and healthcare scoping reviews position the university as a thought leader in one of the field's most consequential application domains. The institution's timely engagement with large language models, including critical analysis of ChatGPT, further reflects intellectual agility. With over 200 citations on multiple flagship papers and contributions spanning industrial IoT, soft robotics, and cognitive science, QMUL offers prospective students and collaborators a rich, well-funded ecosystem where interdisciplinary curiosity is not just welcomed—it is institutionally ingrained.

Research Focus

Key Achievements

61
H-Index
504
Papers
13,508
Total Citations
396
Faculty & Researchers
🏆 Most Cited Paper
Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing
486 citations · 2015
📊 Avg Citations/Paper: 27
📈 Most Prolific Year: 2022 (57)
🔬 Research Focus: Computer science, Artificial intelligence, Robot, Engineering, Psychology, Human–computer interaction

Top Papers

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    ChatGPT: Vision and challenges
    217 citations · 2023
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Faculty & Researchers

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