
Rafael Pires Miranda
Aluno de Doutoramento
Centro de Estudos de Gestão do Instituto Superior Técnico
Rafael Miranda is a researcher at the Centre for Management Studies at Instituto Superior Técnico (CEGIST) and a PhD candidate in Engineering and Management at IST. His PhD research, in collaboration with Siemens Healthineers and under the supervision of Mónica Oliveira, Filipa Matos Baptista, and Isabel Albuquerque, focused on "Developing approaches for continuously monitoring and evaluating integrated remote care interventions."
He holds an MSc in Biomedical Engineering from IST. During his MSc research, he collaborated with Luz Saúde and INESC-ID to develop a deep learning model for multi-label ICD-9 classification of hospital discharge summaries. Rafael also gained professional experience as a Business Intelligence Developer at CUF Hospital Group (2018-2020) and, at Siemens Healthineers, he was responsible for ActExcell projects as part of the Enterprise Services team (2021-2025).
Rafael's contributions to his field include the publication of 3 articles in high-quality health policy journals and presentations at several national and international conferences. Additionally, he has co-supervised 3 master's students and serves as a teaching assistant at IST for the "Engineering, Decision, and Public Policies" curricular unit. His primary research area focuses on integrating multicriteria decision analysis, value-based business intelligence, and stakeholder engagement to advance health technology assessment.
Publicações
Telemedicine and e-Health | 2024
Health Policy | 2023
International Journal of Health Policy and Management | 2023
Grupos de Investigação
DECISING – DECISion science and management engineerING
Projects
SCOPE-Spatial Data Sciences for COVID-19 Pandemic
Spatial Data Sciences (SDS) can provide significant insights into explaining spatial patterns of infectious diseases, understanding and predicting spatio-temporal transmission dynamics, predicting and monitoring the impact of control interventions, which are driven by geographical factors, designing and evaluating optimal resources allocation strategies and cost-effectiveness analyses that incorporate a spatial component and analysing inequities in healthcare based on geography.