Senior Lecturer in Computer Science
I hold a PhD in Artificial Intelligence from the University of Leeds, an MSc in Advanced Software Engineering from Bournemouth University, and a BSc (Hons) in Computer Science from the University of Sunderland.
Prior to my current role, I worked for several institutions and in various capacities since 2000 including Academic Fellow at the University of Edinburgh, Research Associate at Newcastle University, Visiting Scientist at Harvard University, Consultant at London School of Hygiene and Tropical Medicine, and Data Science Manager in Ghana, Africa.
I currently have the following affiliations and membership:
- Gates Sr. AD Fellow
- Associate Member of Royal Society of Medicine
- Member of British Computer Society
- Member of Scottish Dementia Research Consortium
- Member of Alzheimer’s Research UK Scotland Network
- Member of Brain Health Scotland Expert Hub
- Member of Collaboration for Alzheimer Prevention Data Sharing Working Group
- Honorary Academic Fellow, Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences | University of Edinburgh Medical School
- Adjunct Prof , School of Allied Health Sciences, University of Cape Coast, Ghana
Teaching and supervision
I am the Module Leader for:
- CET140 Specialist Project
- FDN006 Foundations of Computing
I supervise MSc students on:
Research interests for potential research students
My research interest is in applied AI and data science with a focus on brain health. I am also interested in the privacy of AI models within the context of trustworthy AI and data protection.
I am a member of a PhD Advisory Committee at Ionian University, Greece.
I am open to PhD student research supervision – please get in touch if interested in pursuing a PhD.
Research
Current research projects as Principal Investigator:
- The Ghana Prevent Programme: a multicentre study involving three UK and two international institutions.
- Explainable AI for ADDR with funding support from Alzheimer's Disease Data Initiative and the Bill & Melinda Gates Foundation
Past research projects
- AI Model Inferencing Project: a Fellowship grant funded by Information Commissioner’s Office of the UK
Publications
Article
Widera, P, Welsing, Paco M.J., Danso, S. O, Peelen, Sjaak, Kloppenburg, Margreet, Loef, Marieke, Marijnissen, Anne C., van Helvoort, Eefje M., Blanco, Franciso J., Magalhães, Joanna, Berenbaum, Francis, Haugen, Ida K., Bay-Jensen, Anne-Christine, Mobasheri, Ali, Ladel, Christoph, Loughlin, John, Lafeber, Floris P.J.G., Lalande, Agnès, Larkin, Jonathan, Weinans, Harrie and Jaume, Baccardit (2023) Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study. Osteoarthritis and Cartilage Open, 5 (4). p. 100406. ISSN 2665-9131
Ritchie, Craig W, Wells, Katie, Gregory, Sarah, Carriere, Isabelle, Danso, Samuel O, Driscoll, David, Dounavi, Maria-Eleni, Hillary, Robert, Koychev, Ivan and Lawlor, Brian (2023) The PREVENT Dementia programme: Baseline demographic, lifestyle, imaging and cognitive data from a midlife cohort study investigating risk factors for dementia. medRxiv.
Danso, Samuel O, Manu, Alexander, Fenty, Justin, Amanga-Etego, Seeba, Avan, Bilal Iqbal, Newton, Sam, Soremekun, Seyi and Kirkwood, Betty (2023) Population cause of death estimation using verbal autopsy methods in large-scale field trials of maternal and child health: lessons learned from a 20-year research collaboration in Central Ghana. Emerging themes in epidemiology, 20 (1). pp. 1-10. ISSN 1742-7622
Danso, Samuel O, Zeng, Zhanhang, Muniz-Terrera, Graciela and Ritchie, Craig W (2021) Developing an explainable machine learning-based personalised dementia risk prediction model: A transfer learning approach with ensemble learning algorithms. Frontiers in big Data, 4. p. 613047. ISSN 2624-909X
Book Section
Danso, Samuel O, Prattipati, Sindhu, Alqatawneh, Ibrahim and Ntailianis, Georgios (2024) Exploration of Machine Learning and Deep Learning Architectures for Dementia Risk Prediction Based on ATN Framework. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-7. ISBN 979-8-3503-6088-2
Luo, Zeqi and Danso, Samuel O (2024) Exploring Risk Factor Interactions across the Development Stages of Dementia using an Explainable Machine Learning Model. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-6. ISBN 979-8-3503-6088-2
Danso, Samuel O and Luo, Zeqi (2024) Exploring Risk Factor Interactions across the Development Stages of Dementia using an Explainable Machine Learning Model. In: 2024 29th International Conference on Automation and Computing. IEEE. (In Press)
Danso, Samuel O, Prattipati, Sindhu, Alqatawneh, Ibrahim and Ntailianis, Georgios (2024) Exploration of Machine Learning and Deep Learning Architectures for Dementia Risk Prediction Based on ATN Framework. In: 2024 29th International Conference on Automation and Computing. IEEE. (In Press)
Conference or Workshop Item
Butler, Joe, Owobowale, Adewale Samuel, Watermeyer, Tamlyn, Danso, Samuel O and Parra-Rodriguez, Mario (2024) Developing an AI algorithm to detect predictors of poor performance in a self-administered, web-based digital biomarker for Alzheimer’s Disease: proof of concept. In: AAIC 2024: Alzheimer's Association International Conference, 28 Jul - 01 Aug 2024, Philadelphia. (In Press)
- Applied AI and Machine Learning
- Natural Language Processing and Applications
- The Human Factors of Cybersecurity
- Corpus and Computational Linguistics for Text Analytics
- Brain Health
- Reviewer for grant applications: UKRI
- Co-Guest Editor, Special Collection on Paradigms of Global Health: Sage Publications
- Journal reviewer: Brains Communication