PhD Student at Medical University of Innsbruck, Austria
Sara Naccour is a highly motivated researcher and computer scientist whose expertise lies at the intersection of mathematics, computer science, and biomedical applications. With a strong foundation in applied mathematics and computer science, she has advanced into research in machine learning with a specialized focus on oncology within the field of ear, nose, and throat (ENT) medicine. Her academic journey has been marked by excellence, as she successfully transitioned from theoretical and applied mathematics to computer science, and then into biomedical machine learning applications. Sara’s research contributions demonstrate her commitment to bridging computational sciences and healthcare, with the ultimate goal of improving cancer diagnosis and treatment.
Professional Profile
ORCID
Education
Sara’s academic path began with an early immersion in mathematics, which shaped her analytical and problem-solving mindset. She completed undergraduate and graduate studies in mathematics, focusing on both fundamental theories and applied aspects. Building upon this solid base, she pursued computer science, where she developed technical skills in programming, software engineering, and system design. Her multidisciplinary knowledge enabled her to understand the complexities of both abstract theory and practical application. Eventually, she advanced to doctoral research, where she specialized in machine learning with applications to ENT oncology. This progression reflects her unique trajectory of integrating mathematics, computing, and medical sciences, which has positioned her as a researcher capable of developing innovative computational models with real-world healthcare applications.
Experience
Sara has gained extensive professional experience that bridges academic excellence with industry-level challenges, contributing to diverse software development projects such as a banking management system built with HTML, CSS, PHP, and MySQL alongside a customer-focused Android application, a user-centered travel agency website interface, and an airline reservation system integrating Java and SQLite. Her technical adaptability and collaborative approach are further complemented by her role as a senior project manager, where she has led teams, managed resources, and aligned technical solutions with organizational goals. This unique combination of hands-on software engineering and leadership in project management reflects her ability to balance academic innovation with practical execution.
Research Focus
Sara’s primary research focuses on applying machine learning to ENT oncology, where she explores how computational intelligence can support early diagnosis, prognosis, and treatment optimization for head and neck cancers by leveraging statistical modeling, pattern recognition, and advanced computational methods to detect subtle medical data patterns that aid clinical decision-making. Alongside her biomedical research, she maintains strong academic interests in mathematics, with her master’s thesis addressing eigenvalue problems of the Laplacian operator on manifolds with foliated boundaries, advancing the field of geometric analysis. She has also pursued advanced training in partial differential equations (PDEs), covering parabolic and hyperbolic equations, biological applications, and hyperbolic systems in applied sciences, a mathematical foundation that continues to reinforce the theoretical depth and rigor of her computational models in oncology research.
Publication Top Note
Title: Machine Learning-Based Classification of Cervical Lymph Nodes in HNSCC: A Radiomics Approach with Feature Selection Optimization
Authors: Sara Naccour; Assaad Moawad; Matthias Santer; Daniel Dejaco; Wolfgang Freysinger
Summary: This article introduces a radiomics-based machine learning framework to classify cervical lymph nodes in head and neck squamous cell carcinoma (HNSCC). Using optimized feature selection, the model enhances diagnostic accuracy and reduces redundancy in imaging data, providing a non-invasive decision-support tool for oncology treatment planning.
Conclusion
In summary, Sara Naccour is a dynamic researcher and professional who has successfully integrated mathematics, computer science, and machine learning into the biomedical domain. Her academic and professional trajectory reflects a rare blend of theoretical depth, technical expertise, and practical application, particularly in the area of ENT oncology. Through her research, she contributes not only to advancing computational methods but also to improving patient care by bringing innovative machine learning solutions into medical practice. Her ability to balance interdisciplinary knowledge, leadership in project management, and continuous professional development makes her a highly deserving candidate for recognition through this award.