University of Nottingham Ningbo ChinaResearch-CentresAI Research InstituteResearch cases

Research cases

CFFormer: Cross CNN-Transformer channel attention and spatial feature fusion for improved segmentation of heterogeneous medical images Artificial Intelligence

CFFormer Image (Click the image to enlarge)

Medical image segmentation is an important part of computer-aided diagnosis, as it helps identify the size and location of lesions and supports clinical decision-making. However, accurately marking these regions often depends on image quality and the experience of radiologists, which can increase the workload in healthcare settings. Although recent advances have improved performance, many existing methods still struggle with low-quality images, where unclear boundaries and noise make it difficult to detect lesions reliably.

To address this issue, we propose a new model called CFFormer, which is designed to better handle blurred areas and capture important information from the entire image. We evaluate the model across five types of medical imaging and eight datasets, and the results show that it performs more reliably than existing approaches, especially on low-quality images. We expect this work to provide a useful reference for future research in medical image segmentation and contribute to the development of more robust computer-aided diagnosis systems.

Jiaxuan Li
Jiaxuan Li

PhD student at the University of Nottingham Ningbo China, supervised by Professor Sean He. Completed both undergraduate and master’s degrees at the University of New South Wales. Research focuses on medical image segmentation and self-supervised learning.

Publication

Falling out with AI-buddies: The hidden costs of treating AI as a partner versus servant during service failure

AI difference Image (Click the image to enlarge)

This research examines how people interact with AI virtual assistants when things go wrong. Companies often design AI to feel more human-like, sometimes presenting it as a “partner” that works with users, rather than a “servant” that simply follows instructions. While this partner-like framing is usually thought to improve user experience, this study shows that it can have unexpected downsides. Across a series of experiments, the researchers find that when an AI system is seen as a partner (versus servant), users are more likely to blame themselves when a service fails.

This happens because people begin to feel psychologically connected to the AI, almost as if it is part of themselves. As a result, when something goes wrong, the failure feels more personal. However, this also reduces users’ confidence in their ability to use the AI and makes them less willing to use it again. The research also shows that companies can reduce the negative effects of failure by emphasizing that the AI is capable of learning and improving over time. Overall, the study highlights a hidden trade-off: making AI feel more like a human partner can strengthen relationships in good situations, but may backfire when problems occur.

Author List: Bo Huang, Sandra Laporte, Sylvain Sénécal and Kamila Sobol

Bo Huang
Bo Huang

Bo Huang is an Assistant Professor in Marketing at Nottingham University Business School China. His research interests include consumer-technology interaction and services marketing, with a particular focus on service failure. His research work has been published in word-leading journals such as International Journal of Research in Marketing, International Journal of Production Management, Journal of Interactive Marketing, Psychology & Marketing, Technological Forecasting & Social Change, among others.

Publication

Ontological capture: AI, childhood, and the algorithmic governance of becoming

Ontological capture Image (Click the image to enlarge)

This research explores how artificial intelligence (AI) is reshaping childhood, education, and society in ways that go far beyond technology itself. Rather than simply helping people learn or work more efficiently, the study argues that AI systems are beginning to influence how individuals think, feel, and even become who they are. At the heart of the paper is the idea of ‘Ontological Capture’. This is the notion that algorithmic systems do not just guide behaviour, but gradually shape the very conditions of human experience. In particular, the research shows how children growing up with AI-driven platforms are increasingly influenced by systems that predict, guide, and subtly control their actions.

This can lead to what we call the ‘algorithmic citizen’: a person who becomes accustomed to responding quickly, following prompts, and relying on automated systems rather than independent judgement.

The study also highlights how AI compresses time and attention, encouraging constant responsiveness and reducing opportunities for reflection, imagination, and meaningful interaction. Over time, this risks weakening key human capacities such as critical thinking, empathy, and civic engagement.

In response, the research proposes a new approach to educational leadership based on stewardship. This involves protecting spaces for human connection, creativity, and thoughtful engagement: through practices such as storytelling, play, and attention to the natural world. Rather than nostalgia, these are presented as essential ways of sustaining human agency and democratic life in an increasingly automated world.

Overall, the research reframes AI in education as a deeply human issue, asking: what kinds of people (and futures), are being created in an age of intelligent machines?

Author List: Alexander Gardner-McTaggart and Carmen Blyth

Alex McTaggart
Alex McTaggart

Alex McTaggart is an Associate Professor of Educational Leadership and Human Futures. His research explores educational leadership in globalising contexts, with a growing focus on emerging challenges such as artificial intelligence and the climate crisis. His work examines how these forces are reshaping education, leadership, and the conditions of human development.

He previously served as Academic Lead for Transnational Education within the Flexible Learning team at the University of Manchester, where he contributed to the development of international and digital education strategies. This was followed by a senior leadership role as Dean of Arts and Social Sciences at the British University of Bahrain, where he led academic programmes and faculty development.

Across these roles, his work reflects a sustained commitment to educational leadership that is internationally grounded, intellectually rigorous, and attentive to the ethical and societal implications of contemporary global challenges.

Publication

Becoming Tech-savvy: Egyptian Journalists’ Perceptions Towards the Acceptance of Automated Journalism

Tech Savvy Image (Click the image to enlarge)

In recent years, Egypt has taken notable initiatives to build its AI strategy in different sectors, and the government has paid attention to develop the country’s sectoral strengths using AI technology. One major aspect of Egypt’s AI strategy is to improve the public perception and understanding of AI technology for better localized applications of technology.

Consequently, according to the 2023 edition of the AI Readiness Index, Egypt has emerged as a regional leader among its North African peers (Oxford Insights 2023). It is among the active MENA countries to follow to the OECD Principles on Responsible AI and has adopted an active approach in shaping the incorporation of AI into its national economy and public service infrastructure.

Interestingly, these developments have triggered debates about the use of automation and AI technologies in the Egyptian news media landscape. However, scholarly work into journalists’ readiness and perceptions towards the practice of automated journalism is still limited in Egypt. Therefore, this study recognizes the timely need to explore different factors pertinent to the acceptance of automated journalism in Egypt. The study draws upon the UTAUT model, which was originally developed in the organizational context to assess the acceptance and adoption of any new technology. Theoretically, hence this study enriches our understanding of the context-specific determinants of the technology acceptance in addition to the UTUAT’s original determinants of perceived usefulness, motivation, job fit, effort expectancy, social influence, and facilitating conditions. This study reveals no relationship between moderating variables of age, gender, qualification, and work experience and the determining constructs including perceived usefulness, effort expectancy, social influence, and facilitating conditions. Also, journalists’ perceptions are not influenced by the type of news organizations in terms of the ownership structure and the language of the news content.

With the AI-driven transformations, it is likely that Egyptian news media can embrace a new competitive environment with transformed workflow of news production in the future, and that is not certainly unique to Egypt alone. News ecologies are changing in different countries where AI is being experimented, such as the US, Britain, Germany, Australia, and China. The matter of concern in the Egyptian context is the extent to which AI-driven changes would affect the ownership structure of news organizations, and whether journalists would have improved levels of freedom of expression and access to information to expand the scope and scale of news products for the local audiences. Hence, despite Egypt’s recent initiatives for capacity building towards the use of AI in different sectors, adopting automated journalism and creating an AI-driven news ecology is not without potential difficulties. It is crucial to acknowledge and address the challenges underpinning automated journalism for gaining its potential benefits.

Author List: Sadia Jamil, Nermeen Alazrak, and Priyanka Kundu

Sadia Jamil
Sadia Jamil

Dr. Sadia Jamil is an Associate Professor at the School of International Communications, The University of Nottingham, Ningbo, China. She is also the former co-director of the Institute of Mobile Studies at UNNC. She earned a PhD in Journalism (University of Queensland, Australia), a Master of Science in Media Management (University of Stirling, Scotland), and a M.A. in Mass Communication (University of Karachi). Dr. Jamil is the recipient of University of Queensland's prestigious awards including UQ's Centennial Award (2010) and IPRS Award (2010). She is the recipient of Cairo Air Crash Journalists Victim Memorial Gold Medal and Sardar Ali Sabri Memorial Gold Medal in Pakistan (2007).

She has taught courses at the Khalifa University of Science and Technology, Abu Dhabi and in the past, at the University of Queensland, Australia.

Dr. Jamil is the Country Representative United Arab Emirates and China of Asian Media Information & Communication Centre (AMIC). She has served as the Vice-Chair of the Journalism Research and Education Section of the International Association of Media & Communication Research (IAMCR) between 2016-2020 and as the Chair of IAMCR's Journalism Research & Education Section between 2020-2025.

Dr. Jamil is also the co-editor of IAMCR and Palgrave book series, the 'Global Transformations in Media and Communication Book Series'. She serves the prestigious IAMCR & Palgrave books series as co-editor.

Dr Jamil is the Deputy Editor of Journal of Applied Journalism & Media Studies, as well as International Journal of Indigenous Language Media and Discourse that is published by North-West University, South Africa. She sits in the editorial boards of international journals including Digital Journalism, Journalism Practice, World of Media, Media Watch and book series Bloomsbury – I.B. Tauris series, Political Communication & Media Practices in the Middle East & North Africa.

Dr. Jamil is one of the Ambassadors of the Digital Poverty Alliance (DPA). She sits in the editorial board of six leading international journals in the areas of journalism, digital media, political communication, and media practices in the Middle East. She is serving as honorary advisor of Media Action Nepal as well.

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