Terese Hellström is a PhD candidate at Eindhoven University of Technology (TU/e) in the Department of Electrical Engineering in the research group Video Coding and Architectures, which is a part of the Signal Processing Systems group. Her research is focused on robust and interpretable AI for cancer detection and diagnosis, specifically focusing on pancreatic cancer and ovarian cancer. Through her close work with clinical researchers, she develops AI solutions that provide meaningful contributions to clinicians to improve patient outcome. Her project is a part of the Advancing Cancer care And Cardiac care through Interpretable AI (ACACIA) project and the Eindhoven Artificial Intelligence Systems Institute (EAISI). As a part of the Eindhoven MedTech Innovation Center (e/MTIC), she develops computer-aided detection (CADe) systems together with partners from the Catharina hospital and the Industrial Design department of TU/e in collaboration with Philips. 

Terese Hellström has a master’s degree in medical physics and is a licensed medical physicist in Sweden. She studied her bachelor's and master's at Stockholm University in collaboration with the Karolinska Hospital, Stockholm, Sweden. She did her master's thesis project at the Maastro Clinic in Maastricht, in a project focused on automatic generation of radiotherapy dose distributions with the thesis titled “Deep-learning based prediction model for dose distributions in lung cancer patients”.