Queensland University of Technology

🇦🇺 AU

Papers

728

Total Citations

37,949

H-Index

80

Researchers

563

About

Queensland University of Technology (QUT) has established itself as a world-leading research institution at the intersection of robotics, artificial intelligence, and intelligent systems, with a particularly distinguished reputation in mobile robotics and autonomous navigation. Based in Brisbane, Australia, QUT's research portfolio spans foundational AI theory through to real-world robotic applications, making it an exceptional destination for both emerging scholars and industry collaborators. QUT's most celebrated contributions lie in biologically inspired robotics and visual navigation. Landmark systems such as SeqSLAM and RatSLAM — the latter drawing on computational models of the rodent hippocampus — have fundamentally shaped how autonomous robots perceive and navigate dynamic environments across seasons and lighting extremes, accumulating nearly 1,400 combined citations. The institution's work on Visual Place Recognition, synthesized in a widely cited survey, has become essential reading for the mobile robotics community. The foundational textbook *Robotics, Vision and Control*, now in multiple editions with over 1,100 combined citations, reflects QUT's commitment to rigorous, accessible knowledge dissemination. Beyond navigation, QUT researchers have driven major advances in agricultural robotics through the DeepFruits system, robotic grasping via the influential GG-CNN framework, and deep learning methodology through a comprehensive review now cited nearly 7,500 times. The institution also pursues cutting-edge work in trustworthy AI for healthcare, smart cities, and multi-target tracking. Home to the Australian Centre for Robotic Vision (ACRV), QUT brings together world-class faculty, state-of-the-art facilities, and strong industry partnerships. Prospective students and collaborators will find an intellectually vibrant environment where foundational research meets transformative real-world impact.

Research Focus

Key Achievements

80
H-Index
728
Papers
37,949
Total Citations
563
Faculty & Researchers
🏆 Most Cited Paper
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
7,484 citations · 2021
📊 Avg Citations/Paper: 52
📈 Most Prolific Year: 2020 (68)
🔬 Research Focus: Computer science, Artificial intelligence, Robot, Engineering, Machine learning, Deep learning

Top Papers

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    Visual Place Recognition: A Survey
    1,071 citations · 2015
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    Robotics, Vision and Control
    671 citations · 2011
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Faculty & Researchers

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