Artificial Intelligence and Robotics

We collaborate extensively with other universities and companies across the world and are active participants in The Alan Turing Institute. Our collaboration with other researchers in Leeds is supported by the Leeds Institute for Data Analytics and Robotics at Leeds.

In the health domain, we lead the UKRI Centre for Doctoral Training in Artificial Intelligence for Medical Diagnosis and Care, partnering with the Leeds Teaching Hospitals NHS Trust and several other key industry and public-sector organisations. We also participate in the MRes in Data Science and Analytics for Health, a part-time course open only to NHS staff.

The research interests of individual members include:

Sharib Ali: Biomedical image analysis; computer vision, machine learning, computational endoscopy and surgery, early cancer detection and intervention, segmentation, 3D reconstruction, pathology.
Mohammad Ammar Alsalka: natural language processing.
Abdulrahman Altahhan: deep reinforcement learning, deep learning, machine learning, intelligent agents, robotics applications.
Eric Atwell: Natural language processing, corpus linguistics, text analytics, Arabic texts.
Brandon Bennett: Reasoning about spatial relations and physical systems, reasoning with vague concepts, semantics of actions and events, non-classical logics, automated deduction.
Andy Bulpitt: computer vision, medical image analysis, machine learning.
Netta Cohen: complex systems, computational neuroscience, neural control of behaviour, biological physics and biomechanics, biorobotics and bio-inspired control (with applications to infrastructure robotics), C. elegans neurobiology, neural circuits and behaviour.
Tony Cohn: knowledge representation & reasoning, ontologies, foundation models, data & sensor fusion, cognitive vision, spatial representation & reasoning, geographical information systems, robotics.
Marc de Kamps: computational neuroscience, artificial intelligence, machine learning.
Vania Dimitrova: knowledge capture, text analysis, ontological modelling, information exploration, user/group modelling, user-adapted interactive systems, decision support systems, intelligent learning environments.
Toni Lassila: numerical algorithms; computational fluid dynamics; reduced order models; cardiovascular modelling; generative deep learning; virtual in-silico trials; physics-informed neural neural networks.
Ping Lu: medical image analysis, machine learning, computer vision, cardiovascular imaging, biomedical signal processing.
Mehmet Dogar: robotics, object manipulation, manipulation planning and control, learning for object manipulation, motion planning, grasping.
David Hogg: computer vision, machine learning, applications to science, engineering and medicine.
Yanlong Huang: deep learning, imitation learning, reinforcement learning.
Owen Johnson: process analytics (including data and process mining, modelling, conformance, simulation and visualisation), Electronic Health Record (EHR) systems, health informatics strategy and implementation.
Derek Magee: medical image analysis, segmentation, activity analysis.
Nabi Omidvar: optimisation, AI in financial technology.
Rafael Papallas: robotics, manipulation planning, motion planning, motion control.
Evangelos Pournaras: distributed intelligence, trustworthy AI, blockchain, collective decision making; digital democracy; computational social systems, Internet of Things, Smart Cities, Smart Grids.
Arash Rabbani: 3-D image analysis, machine learning, modelling of porous materials, medical image analysis.
Nishant Ravikumar: machine learning, computational medicine.
Duygu Sarikaya: surgical vision and perception, computer assisted surgery, medical image computing, computer vision, generative learning, deep learning, machine learning.
John Stell: artificial intelligence, qualitative spatial reasoning, mereotopology, knowledge representation, logic, spatial representation in the digital humanities.
Zheng Wang: distributed systems, computing systems, compilers, machine learning, artificial intelligence, parallel programming, programming languages.

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Joining us

If you would like to join us as a PhD student, please contact a theme member with interests closest to your own.