About
Emir Konuk is a Postdoctoral Researcher at KTH Royal Institute of Technology's Division of Computational Science and Technology, funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP). His research focuses on generative models, inverse problems, and generalization in deep learning, with applications in medical imaging and healthcare. He has contributed to foundational studies on human-AI collaboration and uncertainty estimation in clinical contexts. Additionally, he teaches Applied Programming and Computer Science and Foundations of Machine Learning at KTH.
Recent work includes advancements in offline foundation features using tensor augmentations and international validation of AI-driven ultrasound systems for ovarian cancer detection. His publications span top venues like MICCAI and NeurIPS.
Konuk holds a Doctoral Thesis (2024) titled "Robust and generalizable AI for medical image processing", emphasizing translational AI for healthcare challenges. Collaborations include multi-center clinical trials and theoretical contributions to neural network architecture design.
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