Mirjam Jonkman

Mirjam Jonkman serves as an Adjunct Senior Lecturer in Engineering within the Faculty of Science and Technology, specializing in biomedical engineering and health informatics. Her research applies machine learning and signal processing to develop practical solutions for biomedical challenges including cancer detection, chronic kidney disease modeling, and cyber security applications.

Her research program focuses on:

• Prediction and detection of abnormalities in biosystems using EEG and medical imaging
• Development of efficient deep learning models for clinical diagnostics
• Explainable AI implementations ensuring clinical trustworthiness
• Real-world translation of AI techniques to medical and security domains

Analysis of her 88 publications reveals dominant trends in medical AI applications since 2023, with emphasis on transformer models, attention mechanisms, and computational efficiency for cancer diagnostics, organ segmentation, and disease classification. Her work consistently bridges technical innovation with clinical relevance across oncology, radiology, and gastroenterology.

Jonkman has supervised 8 students and led significant research projects including the Rainmaker Start-up for kidney disease modeling (2021-2022) and a Bronchiectasis diagnostics system (2022-2023). Her collaborative approach involves interdisciplinary teams with medical professionals and computer scientists, evidenced by multi-PI projects addressing real healthcare challenges through AI innovation.