Tanja Alderliesten is Professor of Translational Artificial Intelligence in Radiotherapy at the Department of Radiation Oncology, Leiden University Medical Center (LUMC), where she leads the AI-based Innovations research group. She is a programme committee member of the Real-World Applications (RWA) track of the Genetic and Evolutionary Computation Conference (GECCO) and the SPIE Medical Imaging: Image Processing Conference, and a reviewing committee member of the European Society for Radiotherapy and Oncology (ESTRO) Congress.

More information about Tanja Alderliesten

Tanja Alderliesten is Professor of Translational Artificial Intelligence in Radiotherapy at the Department of Radiation Oncology, Leiden University Medical Center (LUMC), where she leads the AI-based Innovations research group. 

She is a programme committee member of the Real-World Applications (RWA) track of the Genetic and Evolutionary Computation Conference (GECCO) and the SPIE Medical Imaging: Image Processing Conference, and a reviewing committee member of the European Society for Radiotherapy and Oncology (ESTRO) Congress.

Artificial intelligence (AI)

Artificial intelligence (AI) offers substantial opportunities for advancing digital healthcare. Yet, translating these opportunities into clinical practice is challenging, requiring both adaptation of existing technologies and developing entirely new approaches. This is the core of Tanja Alderliesten’s research agenda. A key focus is thereby on radiation oncology, particularly the automation and enhancement of tasks in image-guided radiation therapy workflows that are predominantly manual, are resource-intensive, or are insufficiently supported by current software solutions. By establishing an innovation ecosystem and driving co-creation with clinicians, technical specialists, and AI researchers, she ensures that resulting technologies are scientifically rigorous, clinically relevant, and ultimately ready for deployment in practice.

Her research portfolio spans (semi-)automatic medical image analysis, optimization of radiation treatment planning, and the design of novel explainable AI methods for predictive modeling aimed at enabling more individualized clinical decision-making. A prominent example of clinical impact is the AI-based brachytherapy treatment-planning system BRIGHT, that she co-developed with Centrum Wiskunde & Informatica (CWI) and Amsterdam UMC. BRIGHT introduces a novel paradigm by generating multiple optimized treatment plans that the planning team can choose from in an insightful way, and has been in clinical use for prostate cancer at Amsterdam UMC since 2020. Under her leadership, BRIGHT has been extended to cervical cancer and is currently being prepared for clinical implementation at both Amsterdam UMC and LUMC.

Academic career

Tanja Alderliesten holds a Master of Science in Computer Science from Utrecht University. She conducted her PhD research at the Image Sciences Institute (ISI), an interdisciplinary research institute within the University Medical Center Utrecht, and was awarded a PhD from Utrecht University, Faculty of Medicine. She defended her PhD thesis, “Simulation of minimally-invasive vascular interventions for training purposes”, on December 7, 2004. She then worked as a postdoctoral researcher at the Netherlands Cancer Institute – Antoni van Leeuwenhoek Hospital (NKI-AVL) in the departments of Radiology and Radiation Oncology, followed by a position as senior researcher at the department of Radiation Oncology, Amsterdam UMC, location Academic Medical Center. In 2019, she joined LUMC as an associate professor and became full professor in 2025.