معرفی
Matthew Blaschko is a Senior Lecturer BOF at KU Leuven, affiliated with the Department of Electrical Engineering (ESAT) within the Faculty of Engineering Sciences. He directs the KU Leuven ELLIS unit and serves as a fellow in the ELLIS Health program, part of the European Laboratory for Learning and Intelligent Systems. As a Core PI in the Flanders AI Research Program, he leads work packages for Decision Support Systems and Medical Imaging. He is also a member of the KU Leuven Institute for Artificial Intelligence and co-leads the working group on Machine Learning and Data Science.
- Habilitation (HDR) from École Normale Supérieure de Cachan
- Newton International Fellow at University of Oxford
- Dr. rer. nat. from Max Planck Institutes Tübingen (awarded by Technische Universität Berlin)
- M.S. from University of Massachusetts Amherst
- B.S. from Columbia University
Blaschko's research focuses on machine learning, computer vision, and medical image analysis, with particular expertise in uncertainty quantification in deep neural networks and trustworthy AI for healthcare applications. His work bridges theoretical foundations with practical implementations, developing methods for calibration, uncertainty estimation, and efficient model deployment. He has made significant contributions to neural network architectures, loss functions, and evaluation metrics for medical imaging tasks, with applications spanning Alzheimer's disease research, surgical phase recognition, and ophthalmic image analysis.
His recent publications reveal a strong emphasis on calibration methods, uncertainty quantification, and medical applications of AI. The research spans diverse areas including Alzheimer's disease analysis, Bayesian optimization, novel view synthesis, knowledge extraction from text, and surgical phase recognition. Many papers focus on improving model reliability and safety for healthcare applications, reflecting his commitment to developing trustworthy AI systems that can be deployed in clinical settings.
- Best Student Paper Award, ECCV 2008
- Université Paris-Saclay STIC Doctoral School Best Scientific Contribution Award
- Best paper award, CVPR 2008
- Best paper award, Benelearn 2014
Blaschko actively mentors numerous PhD and MSc students, with current advisees working on topics ranging from uncertainty in deep neural networks to medical image analysis and AI for healthcare. He leads multiple significant research projects including 'onzekerheid in diepe neurale netwerken' (2025-2029), 'Trustworthy AI for Medical Image Analysis and Computer Vision' (2025), and 'Van metingen naar biomarkers in medische beeldanalyse' (2024-2028). His research is supported by the Flanders AI Research Program and other substantial funding sources.
As director of the KU Leuven ELLIS unit and a key member of the KU Leuven Institute for Artificial Intelligence, Blaschko leads a vibrant research team focused on machine learning and data science. His laboratory develops cutting-edge AI technologies with practical applications, particularly in healthcare. Technology from his research has been incorporated into MONA, software for ophthalmic image analysis, demonstrating the real-world impact of his work.
