Professor Feng Dong

Computer and Information Sciences


Personal statement

Feng Dong joined the University of Strathclyde from 2nd Sept 2019. He is currently a professor at the Department of Computer and Information Sciences. He was awarded a PhD from Zhejiang University, China.  His recent work has also developed new areas in visual analytics, pattern recognition, AI, parallel computing and GPU, image-based rendering and figure animation.

In brief, Feng Dong's profile can be summarised as follows:

  • Leading and managing collaborative research projects and teams across Europe to conduct externally funded cross-disciplinary research projects in health technology and computational creativity, with a substantial track record in attracting external research funding by gaining around £7 million external research fund (as PI) from the EC and EPSRC since Sept 2007. These include 5 European grants and 3 EPSRC grants (as PI) and project coordinator & leading investigator for 4 collaborative research projects.

  • Network with leading research organisations and researchers across the UK and Europe through jointwork in research grants.

  • Collaboration with medical professionals through collaborative research projects and joint clinical pilots, and active engagement with the end users to empower the society at large in healthcare, targeting significant impact beyond academia.

  • Close working relationships with the industry through joint work in research grants.

  • Over 15 years of teaching practice in the UK with substantial experience in the design and delivery of a wide range of research-informed teaching activities at both post-graduate and under-graduate levels.

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Area of Expertise

Main knowledge contributions towards intelligent data analytics fall into a range of areas including:

-   Knowledge discovery in AI for healthcare to support patient self-management of general health and chronic conditions, involving smart monitoring, data validation from heterogeneous sensors,  personal activity and event recognition,  health information recommendation, personal health status estimation and serious gaming.

-    Intelligent data analytics for computational creativity in AI by coordinating the EC-funded Dr Inventor research project and leading the development of the Dr Inventor platform. The Dr Inventor surrogate acts as a personal research assistant, utilising machine-empowered search and computation to bring researchers extended perspectives for scientific innovation by informing them of a broad spectrum of relevant research concepts and approaches, by assessing the novelty of research ideas, and by offering suggestions of new concepts and workflows with unexpected features for new scientific discovery.

-   Visualization and parallel computing (GPU) for large-scale medical data, , including transfer function for feature enhancement in volume rendering of medical data; viewpoint selection and lighting design for volume rendering of medical data; Non-photorealistic volume rendering for feature enhancement from medical data; GPU-based iso-surface extraction from volume data and automated GPU-based parallelisation for images operations and image feature extractions.

-   Visual analytics for health data to support the navigation, query and understanding of health records, clinical driven research in predictive models for cancer growth in response to treatment options, and the discovery of data patterns within patient cohort in both clinical and lifestyle domains

-   Computer vision and machine learning for computer graphics research, including sparse modelling and representation for human motions,  blind motion deblur for natural images,  adaptive texture synthesis for high fidelity images and image based rendering based on inferences in machine learning

-    Health data interoperability to support long-term collection of personal health information by aggregating  electronic and personal health records, lifestyle data and drug information in a decentralised approach to offer easy access to personal medical history, empower the patients, improve self-management, and facilitate clinical research with significant advantages in privacy, security, safety, transparency and data integrity.

The recent active research projects include: 

REAMIT- The project proposes to adapt and apply existing innovative technology to food supply chains in NWE to reduce food waste and hence improve resource efficiency (Project Information: European Commission Interreg North-West Europe, €608,118 for the local institution, from 2019 to 2022.) - Role: Co– Investigator

Aquaculture 4.0 -- The project will bring together several cutting-edge digital technologies including sensor networks for online monitoring, diagnosis, control and optimisation of aquaculture production, 5G communication for low-latency, high data rate, real-time transmission of big data, internet-of- things (IoT) system for big data storage, analytics, modelling and model-based decision making. By integration of these digital technologies, the project will deliver a prototype system of precision Aquaculture 4.0, and demonstrate the economic, environmental and social benefits through pilot applications in China (Project Information: Innovate UK, over £223,209 for the local institution, Feb 2019 – Dec 2021) - Role: Co-Investigator


  • PhD in Computer Science, Zhejiang University, China
  • PGCERT Higher Education 
  • The Higher Education Academy Fellow -
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Assessing the needs of clinicians in adult critical care in Scotland for a sepsis fluid management Artificial Intelligence tool using a human factors approach
Preston Kate, Dunlop Emma, Ferguson Aimee Margaret Denver, MacLellan Calum Robert, Dong Feng
2023 Digital Heath & Care Fest (2023)
Breast cancer survival analysis with molecular subtypes : an initial step
Zhang Lingli, Wu Jiaiun, Zhao Youbing, Hu Wenxian, Qin Aihong, Dong Feng, Liu Enjie, Zeng Hao, Xie Hao, Du Hui
2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE), pp. 363-366 (2022)
A randomised-controlled feasibility study of the REgulate your SItting Time (RESIT) intervention for reducing sitting time in individuals with type 2 diabetes : study protocol
Bailey Daniel P, Edwardson Charlotte L, Pappas Yannis, Dong Feng, Hewson David J, Biddle Stuart J H, Brierley Marsha L, Chater Angel M
Pilot and Feasibility Studies Vol 7 (2021)
Best practices for authors of healthcare-related artificial intelligence manuscripts
Kakarmath Sujay, Esteva Andre, Arnaout Rima, Harvey Hugh, Kumar Santosh, Muse Evan, Dong Feng, Wedlund Leia, Kvedar Joseph
npj Digital Medicine Vol 3 (2020)
Randomised controlled feasibility study of the MyHealthAvatar-Diabetes smartphone app for reducing prolonged sitting time in Type 2 diabetes mellitus
Bailey Daniel P, Mugridge Lucie H, Dong Feng, Zhang Xu, Chater Angel M
International Journal of Environmental Research and Public Health Vol 17 (2020)
Patient empowerment for cancer patients through a novel ICT infrastructure
Kondylakis Haridimos, Bucur Anca, Crico Chiara, Dong Feng, Graf Norbert, Hoffman Stefan, Koumakis Lefteris, Manenti Alice, Marias Kostas, Mazzocco Ketti, Pravettoni Gabriella, Renzi Chiara, Schera Fatima, Triberti Stefano, Tsiknakis Manolis, Kiefer Stephan
Journal of Biomedical Informatics Vol 101 (2020)

More publications

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Research Interests

Intelligent data analytics and visualization to addressed a range of issues in:

  • AI to support knowledge discovery
  • Visual data analytics
  • Computer vision and image analysis
  • Health data interoperability
  • Medical visualization and computer graphics

Professional Activities

AI-Powered Clinical Trials: Emulating Real-World GLP-1 Efficacy with Synthetic Patient Populations using Causal Effect Learning
Assessing the needs of clinicians working in adult critical care in Scotland for a sepsis fluid management Artificial Intelligence tool.

More professional activities


DTP 2224 University of Strathclyde | Cummings, Joshua
Oliveira, Monica (Principal Investigator) Dong, Feng (Co-investigator) Cummings, Joshua (Research Co-investigator)
01-Jan-2022 - 01-Jan-2026
Virtual Clinical Trial Emulation with Generative AI Models
Dong, Feng (Principal Investigator) Maguire, Roma (Co-investigator)
31-Jan-2022 - 27-Jan-2023
Clinical Imaging Innovation and Partnership award (SYNAPSE)
Banger, Matthew (Principal Investigator) Riches, Phil (Principal Investigator) Banger, Matthew (Co-investigator) Dong, Feng (Co-investigator) Riches, Phil (Co-investigator)
01-Jan-2021 - 30-Jan-2021
EPSRC Centre for Doctoral Training in Future Power Networks and Smart Grids | MacLellan, Calum Robert
Dong, Feng (Principal Investigator) McConnell, Gail (Co-investigator) MacLellan, Calum Robert (Research Co-investigator)
01-Jan-2018 - 01-Jan-2023
Empowering patients and strengthening self-management in cancer diseases
Dong, Feng (Principal Investigator)
EC funded, about 4 Million Euro funding, local institution >600K Euro, Grant Agreement no. 643529,9 partner institutions, 3.5 years, 2015 – 2018) Role: Local PI and work package leader
01-Jan-2015 - 31-Jan-2018
An interoperability hub for aggregating lifelogging data from heterogeneous sensors and its applications in ophthalmic care
Dong, Feng (Principal Investigator)
EPSRC funded, about £310K, local institution>£190K, 3 partner institutions, EPSRC, EP/L023830/1, 2014 – 2016 Role: Leading Principal Investigator
01-Jan-2014 - 31-Jan-2016

More projects

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Professor Feng Dong
Computer and Information Sciences

Tel: 548 3409