Jose Sousa

I hold a PhD in Information Systems and Technology from the University of Minho (Portugal, 21/11/2014) and have developed a comprehensive professional background in higher education and research institutions across Europe. My academic career spans more than 20 years, encompassing both permanent and fixed-term appointments in research, as well as leadership roles in infrastructure and technology. I am currently a Principal Investigator (2021–present) at the Sano Centre for Computational Medicine in Krakow, Poland, under a research-focused permanent contract. I also serve as an Associated Researcher (2024–present) at EPQM–CCG/ZGDV ICT Institute, affiliated with the University of Minho, and hold the title of Honorary Lecturer (2022–present) in the Faculty of Medicine, Health and Life Sciences at Queen’s University Belfast, UK, under a non-salaried academic affiliation.

Previously, I served as an Affiliated Researcher (2022–2023) at the University of Glasgow, within the Institute of Infection, Immunity, and Inflammation, where I engaged in a temporary research collaboration. From 2017 to 2021, I held a permanent position as Manager of the Advanced Informatics Core Technology Unit at Queen’s University Belfast, where I led initiatives in data science, clinical research support, and the development of innovative technologies. During the same period, I also served as a Machine Learning and Data Science Expert for Health Data Research UK (HDR UK) at both Queen’s University Belfast and Swansea University. Furthermore, I acted as Chief Technology Officer (2018–2020) for Sonrai Analytics, a university spin-out, and was the Information Systems Director (2005–2017) at I3S – Institute for Research and Innovation in Health, University of Porto, where I led the planning and implementation of scientific computing infrastructure in a large-scale biomedical research environment. In these roles, I have consistently specialised in the scientific subarea of Data Science and Artificial Intelligence, with a particular emphasis on explainable AI, learning from small and incomplete datasets, and developing decision-support systems for health applications.My expertise centres on AI continuous learning, explainable machine learning, and decision-support systems designed for small and incomplete datasets, which pose critical challenges in delivering personalised medicine. Over the years, I have developed innovative tools, including CACTUS (Comprehensive Abstraction and Classification Tool) and SaNDA (Small and Incomplete Dataset Analyser), both of which aim to enhance explainability and robustness in clinical data analysis. These tools have demonstrated strong results in disease risk stratification and classification, particularly in areas such as hematuria and allergies.

My publication record includes Q1 journals such as ACM Transactions on Intelligent Systems and Technology, Information Sciences, and Alzheimer’s & Dementia. My work is characterised by methodological originality, particularly in developing cognitively inspired, explainable systems that emulate human decision-making with limited information and computational resources. My leadership in research is demonstrated through my successful and ongoing coordination of large-scale funded projects, including those with over €2 million in funding from the Foundation for Polish Science, Horizon 2020, and the Polish Ministry of Science and Higher Education. I have also collaborated with industry, notably deploying the CACTUS platform at RANDOX Laboratories in the UK for biomedical research and digital health applications.

I also have a strong track record in team building and mentorship, currently supervising five PhD students, two postdoctoral researchers, and multiple master’s students across institutions in Poland, Portugal, and the UK. I remain committed to gender balance, having achieved 50% gender parity within my team.
I have contributed to the development of international research infrastructure, including the complete design and implementation of information systems at the I3S institute in Porto and advanced data platforms at Queen’s University Belfast. My work has directly supported public health initiatives, particularly during the COVID-19 pandemic, through the creation of AI models for health surveillance and prediction.
As an active member of the international AI community, I am involved in editorial and advisory boards and co-editing an upcoming Springer volume on cognitive information visualisation. I regularly deliver invited talks and educational workshops on AI for biomedicine. My interdisciplinary approach and focus on explainable, actionable AI continue to position me as a leading voice in the development of trustworthy AI systems for health and medicine.