QURAI - Key Persons
Caroline Magg received her bachelor's degree in Technical Mathematics and both her master's degrees Biomedical Engineering and Visual Computing at the TU Vienna, Austria. In her first master thesis, she developed an automatic algorithm for ECG annotations in mice at the AIT Austrian Institute of Technology in Vienna. In her second master thesis, she developed domain adaptation approaches for cross-modal brain tumor segmentation in MRI scans and she designed and implemented an interactive visual analytics application for outcome assessment and multi-model comparison.
In 2022, Caroline joined the qurAI group as PhD candidate. She is working on AI-based prediction of knee implant loosening, under supervision of Clarisa Sánchez. For the project she is working closely together with the orthopaedics department at the Amsterdam UMC - location AMC.
Job Titles:
- Specialist and Data Scientist at Moorfields Eye Hospital
- Student
Dr. Roy Schwartz is a medical retina specialist and data scientist at Moorfields Eye Hospital, London. He studied medicine at the Hebrew University in Jerusalem and was trained in ophthalmology at the Tel Aviv Medical Centre. He later finished a fellowship in medical retina at Moorfields Eye Hospital and is now a retina specialist there. Dr. Schwartz is currently undertaking the AI-Enabled Healthcare centre for doctoral training programme at UCL in London. As part of this programme, he finished his master's degree in AI-enabled healthcare with distinction and is currently undertaking a PhD in the same topic under the supervision of Clarisa Sánchez. Since October 2020 he is also part of the Eye Lab in the qurAI group (University of Amsterdam). The subject of his PhD is "Deep learning, large datasets, genome-wide analysis and histological correlates to determine the role of reticular pseudodrusen in the progression of age-related macular degeneration". In 2019, Dr Schwartz was awarded the inaugural EURETINA Retinal Medicine Clinical Research Funding Grant of 262,112 for this project and serves as its chief investigator.
Job Titles:
- Leader of the AI for Oncology
Louis van Harten studied Electrical Engineering at the Eindhoven University of Technology, specialising in embedded systems and high-performance computing. His bachelor thesis focused on GPU acceleration of scientific simulation software. In 2018, he received his Master of Science degree with honours. In October 2018, Louis joined the Quantitative Medical Image Analysis Group as a Ph.D. candidate; In 2019, he moved with the group to the Amsterdam UMC - location AMC and is now part of the Gastrointestinal lab under supervision of Prof. dr. Ivana Išgum and Prof. dr. Jaap Stoker. His current research centers around development of machine learning based methods for analysis of gastrointestinal motility in the dynamic MRI of the abdomen.
Maria Galanty graduated from the University of Warsaw with two separate Bachelor's Degrees (BSc) in Mathematics and Cognitive Science. Currently, she is finishing her Master's degree (MSc) in Artificial Intelligence at Utrecht University. She joined the qurAI Group as a PhD candidate in June 2022, as a part of the Intensive Care Lab, under the supervision of Clarisa Sanchez. Her PhD is a part of the UvA Research Priority Agenda AI for Health Decision-Making, which is a collaboration between Faculties of Medicine, Science, Humanities and Law. Her main project focusses on the development of AI-driven decision-making coagulation and transfusion strategies serving hospitalized patients that undergo major surgery and have a high risk of bleeding.
Nils Hampe received his Bachelor degree in Physics at the Karlsruhe Institute of Technology, Germany. Seeking for more practically applicable challenges he enrolled in the Master course Medical Engineering at the University of Lubeck, Germany, which he finished with honours in 2019. His Master thesis emerged from a collaboration with Philips Research Hamburg and UMC Utrecht under the title "Deep learning for Electrical Properties Tomography", which lead to a publication in 2020. In 2019, Nils became a PhD candidate at the Quantitative Medical Image Analysis Group (Image Sciences Institute) under supervision of Prof. dr. Ivana Išgum. His research focuses on artificial intelligence for cardiovascular risk assessment. In September 2019, his project got transferred to the Amsterdam UMC where he continues his research on artificial intelligence for cardiovascular risk assessment in the Cardiovascular Lab.
Job Titles:
- Biomedical Engineer
- Student
Pierandrea Cancian (1994) is a Biomedical Engineer and PhD candidate at the CARA Lab. He earned both his Bachelor and Master degree at the Politecnico di Milano. Before starting his position at the CARA Lab Pierandrea worked a mix of industry and research, where he mostly focused on Machine Learning and Computer-vision. The projects he was involved in ranged from segmentation of histopathological images to the detection of external damages in vehicles after car accidents. Since June 2023, Pierandrea works as a PhD candidate on the application of AI methods for the automated analysis of optical coherence tomography (OCT) images. The aim of the research is to develop AI models for artifact detection in OCT images and their correction as well as to determine reliability of the downstream analysis. This research is supervised by Ivana Isgum, Niels van Rooijen and Jos Thannhauser.
Soufiane Ben Haddou completed his Bachelor's degree in Artificial Intelligence in 2021 at the University of Amsterdam, followed by a Master's degree in the same field in 2023 at the same university. During his master's thesis, he focused on mesh reconstruction of the left ventricle from LGE segmentations using a transformer variational autoencoder. He examined how well the latent representation captured the geometry by measuring meaningfulness and representativeness through predictions on the latents and generating new samples respectively. He was supervised by Dr. Erik Bekkers from AMLab and Dr. Fleur Tjong from AUMC.Now embarking on a PhD, Soufiane is working on the prediction of Dilated Cardiomyopathy (DCM), with the goal of prematurely predicting DCM using multimodal solutions. These solutions incorporate various modalities such as MRI, ECHO, ECG, genetic information, and clinical data. His work is under the supervision of Prof. Ivana Isgum, a Professor in AI and Medical Imaging at the University of Amsterdam, and Prof. Connie Bezzina, a professor specializing in the Genetics of Cardiac Disorders.His involvement is with the QurAI group at the University of Amsterdam and Amsterdam UMC. DCM, the focus of his research, is a heart muscle disorder characterized by the thinning and stretching of the heart muscle in the left ventricle, complicating blood supply to the body. The project, ‘DCM-NEXT', aims to develop new models through multimodal deep learning and computer vision for earlier diagnosis and better treatment of DCM, utilizing clinical, imaging (CT, MRI, ECHO), ECG, and genetic data. The project's ambition is to integrate these models to harness the predictive value of each modality.