Postdoctoral researcher at the Division of Medical Radiation Physics, Stockholm University (SU)
Passionate about applying deep learning (DL) and machine learning (ML) methods to cancer imaging analysis
Aims to develop imaging biomarkers for cancer diagnosis, prognosis, staging, progression prediction, treatment response assessment, and radiation therapy planning
Research focuses on brain tumors, lung tumors, bone metastases, head & neck cancers, and lymph node involvement
Works with radiological and molecular imaging modalities including MRI, CT, and PET
Methodologically interested in supervised learning, representation learning, active learning, and federated learning