Deep Learning

Learn to Reason and Explain

Interpretable ML, Disentangled Representation, Fairness

Learn to Recognize

Detection, Classification, Segmentation, Anomaly Detection, Semi-/Weakly-Supervised Learning

Modelling Uncertainty in Deep Learning for Medical Applications

DAAD Funded Project with ETH Zürich and Imperial College London (2020-2022)

Uncertainty Aware Methods for Camera Pose Estimation and Relocalization

BaCaTeC Funded Project with Stanford University and Siemens AG (2020-2021)

Organizing Committee Member at MICCAI DART 2020

Organizing Committee Member at MICCAI DCL 2020

Uncertainty-based graph convolutional networks for organ segmentation refinement

Organ segmentation is an important pre-processing step in many computer assisted intervention and diagnosis methods. In recent years, CNNs have dominated the state of the art in this task. Organ segmentation scenarios present a challenging …