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Cunjia Liu

Prof. at Loughborough University

Loughborough University
Country flagUnited Kingdom

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About

Professor Cunjia Liu is a faculty member at Loughborough University in the UK. His research focuses on advanced robotics, including cooperative aerial manipulation, adaptive path planning for pollution dispersion, and safety-critical control for nonlinear systems. He has published extensively on topics such as motion planning for aerial systems, robotic grasping using deep learning, and multi-robot coordination for environmental monitoring.

Positions (3)

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Cunjia Liu

University Name
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Loughborough University

No summary provided for this position.

NaN years ago

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Tom Stanton

University Name
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Loughborough University

[Fully funded studentship partially funded by NERC, includes a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant (RTSG) of £8,000. International candidates may be eligible for full fee coverage subject to UKRI rules.] This fully funded PhD studentship at Loughborough University offers an exciting opportunity to advance research in environmental monitoring by optimising aerial image analysis for beach litter characterisation and quantification. The project is embedded within a three-year marine litter monitoring campaign on the Isle of Skye, Scotland, and builds on the university’s extensive research in this area, including the '50 Years of Litter on Skye' initiative. The successful candidate will join an interdisciplinary team integrating environmental science, engineering, and social science methodologies, working closely with community partners across Scotland’s west coast. The research will focus on evaluating the efficacy and suitability of digital image collection and analysis for characterising beach litter on heavily-littered coastlines. The project will assess various image capture techniques, including the use of drones and mobile phones, and explore the potential of different sensor types such as RGB and multispectral cameras. The analysis will compare manual digital approaches (e.g., Dot Dot Goose) with the development of automated computer vision algorithms for marine litter characterisation and quantification. Supervision will be provided by Dr Tom Stanton (primary), Prof. Cunjia Liu, Prof. Adrian Spencer, and Dr Nicholas Midgley (Nottingham Trent University), offering a breadth of expertise in environmental science, engineering, and computational methods. The studentship is partially funded by NERC and provides a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant (RTSG) of £8,000. International candidates are eligible, with the university covering the difference between UK and international tuition fees for successful applicants, subject to UKRI funding rules. Applicants should hold or expect to obtain at least a 2:1 degree (or equivalent) in Geography, Environmental Science, Computer Science, Engineering, or a related field, or possess an appropriate Master’s degree. Minimum English language requirements apply. The application process involves completing a CENTA studentship application form (available at https://centa.ac.uk/apply/ ) and submitting it online via the Loughborough University portal, selecting the 'Department of Geography and Environment' and quoting reference CENTA2026-LU09. The deadline for applications is January 7th, 2026, with interviews expected in early February 2026. This studentship is ideal for candidates interested in interdisciplinary research at the intersection of environmental science, computer vision, and community engagement, with a strong commitment to addressing marine litter challenges through innovative technological solutions.

9 months ago

Publisher
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Tom Stanton

University Name
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Loughborough University

This PhD project at Loughborough University aims to optimise aerial image analysis for the characterisation and quantification of beach litter, building on the university’s extensive research into marine litter, including the '50 Years of Litter on Skye' initiative. The research responds to a three-year marine litter monitoring campaign on the Isle of Skye and involves collaboration with community partners across Scotland’s west coast. The project is highly interdisciplinary, integrating environmental science, engineering, and community science methodologies. The successful candidate will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation, focusing on heavily-littered coastlines. The research will assess the practicality of various image capture techniques, including the use of drones and mobile phones, and explore the potential of different sensor types such as RGB and multispectral sensors. Image analysis will involve both manual digital approaches (e.g., Dot Dot Goose) and the development of automated computer vision algorithms for marine litter characterisation and quantification. The project is designed to enhance marine litter monitoring methods and support community-led environmental initiatives. The studentship is partially funded by NERC and provides a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant of £8,000. International candidates are eligible, with the university covering the difference between UK and international tuition fees for successful applicants, subject to UKRI funding rules. Applicants should have at least a 2:1 degree (or equivalent) in a relevant field such as Geography, Environmental Science, Computer Science, or Engineering, and must meet the university’s English language requirements. The position is available full-time (3.5 years) or part-time (7 years), with a start date in October 2026. Applications close on January 7th, 2026, and interviews for shortlisted candidates will be held in February 2026. For application instructions, candidates should complete the CENTA studentship application form and apply online, quoting the reference number CENTA2026-LU09.

9 months ago

Articles (11)

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Collaborators (8)

Wenhua Chen

Loughborough University

UNITED KINGDOM
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Urbano J. Nunes

University of Coimbra

PORTUGAL
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Zhongguo Li

Lecturer (Assistant Professor) in Robotics, Control, Communications and AI

The University of Manchester

UNITED KINGDOM
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Jun Yang

Senior Lecturer

Loughborough University

UNITED KINGDOM
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Cristiano Premebida

Assistant Professor

University of Coimbra

PORTUGAL
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Yunda Yan

Lecturer in Control Engineering

De Montfort University

UNITED KINGDOM
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Yang Liu

University of Huddersfield

UNITED KINGDOM
View details

Song Ma

University College London

UNITED KINGDOM
View details
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