Sayna Rotbei
About me
I am currently a postdoctoral researcher in the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet, focusing on the application of artificial intelligence in healthcare. With an academic background in IT engineering, I have developed a strong interest in leveraging AI to support clinical decision-making and enhance patient outcomes. My research interests lie in interdisciplinary work at the intersection of technology, medicine, and public health, where I aim to contribute to data-driven solutions for real-world healthcare challenges.
Research
My research interests focus on the application of artificial intelligence and machine learning in healthcare, particularly in clinical decision support and outcome prediction. I am especially interested in interdisciplinary approaches that combine medical data, computational models, and public health perspectives to address real-world healthcare challenges.
Teaching
I have supported undergraduate and postgraduate courses in information technology and data processing. I also assist master’s students with their thesis projects, providing guidance on research design and practical implementation.
Articles
- Journal article: EXPERT SYSTEMS WITH APPLICATIONS. 2024;257:125058Rotbei S; Tseng WH; Merino-Barbancho B; Haleem MS; Montesinos L; Pecchia L; Fico G; Botta A
- Journal article: INTELLIGENT SYSTEMS WITH APPLICATIONS. 2023;18:200237Botta A; Rotbei S; Zinno S; Ventre G
- Journal article: JOURNAL OF DECISION SYSTEMS. 2022;32(1):19-48Rouhani S; Rotbei S
- Journal article: DIAGNOSTICS. 2022;12(4):957D'Urso G; Magliacano A; Rotbei S; Iasevoli F; de Bartolomeis A; Botta A
- Journal article: ELECTRONICS. 2020;9(3):516Peral J; Gil D; Rotbei S; Amador S; Guerrero M; Moradi H
- Journal article: JOURNAL OF DECISION SYSTEMS. 2017;26(4):368-393Rouhani S; Rotbei S; Hamidi H
- Journal article: JOURNAL OF MANAGEMENT ANALYTICS. 2017;4(2):182-201Rouhani S; Rotbei S; Shamizanjani M
All other publications
- Book chapter: 9TH EUROPEAN MEDICAL AND BIOLOGICAL ENGINEERING CONFERENCE: IFMBE PROCEEDINGS. 2024;p. 223-234Rotbei S; D’Urso G; Botta A
- Preprint: ELSEVIER BV. 2024Rotbei S; Napolitano L; Zinno S; Collà Ruvolo C; Verze P; Botta A
- Conference publication: 2023;00:1-6Rotbei S; Napolitano L; Zinno S; Verze P; Botta A
- Preprint: ELSEVIER BV. 2023Zinno S; Rotbei S; Gallo L; Botta A; Ventre G
- Preprint: ELSEVIER BV. 2023Zinno S; Rotbei S; Gallo L; Botta A; Ventre G
- Book chapter: NEURAL ENGINEERING TECHNIQUES FOR AUTISM SPECTRUM DISORDER. 2021;p. 77-125Amador S; Polo A; Rotbei S; Peral J; Gil D; Medina J
- Book chapter: NEURAL ENGINEERING TECHNIQUES FOR AUTISM SPECTRUM DISORDER. 2021;p. 55-76Polo-Rodríguez A; Rotbei S; Amador S; Baños O; Gil D; Medina J
- Book chapter: NEURAL ENGINEERING TECHNIQUES FOR AUTISM SPECTRUM DISORDER. 2021;p. 77-125Amador S; Polo A; Rotbei S; Peral J; Gil D; Medina J
- Book chapter: NEURAL ENGINEERING TECHNIQUES FOR AUTISM SPECTRUM DISORDER. 2021;p. 55-76Polo-Rodríguez A; Rotbei S; Amador S; Baños O; Gil D; Medina J
Grants
- The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS)1 October 2026 - 1 October 2028This project develops a multi-modal Mixture-of-Experts (MoE) framework to improve breast cancer recurrence prediction. Integrating histopathology, molecular, radiology, and clinical data, it leverages the CHIME-BC model, multiple-instance learning, and time-to-event loss. Validated across the CHIME, SCAN-B, and AID4BC cohorts, the framework advances precision risk stratification to deliver accessible, equitable prognostic insights directly from routine H&E images.
Employments
- Postdoctoral Researcher, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2026-2028
- Postdoctoral Researcher, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2025-2027
- Postdoctoral Researcher, University of Naples Federico II, 2024-2025
Degrees and Education
- PhD - Information Technology and Electrical Engineering, University of Naples Federico II, 2024