• Deep learning
• Computer Vision
• Medical Imaging

Project Manager for the Helmholtz Transfer Academy "Future Innovators". Interested in anything that can solve problems. Trying to unlock the potential of scientific development to also solve short-term problems of the real-world.

I specialize in harnessing the power of artificial intelligence for the automation of image analysis processes. My expertise encompasses a diverse range of characterization methods, from electron microscopy image analysis to advanced synchrotron tomography investigations. A unifying thread across all …

Combining Physics, Medicine, Computational Science, Computer Science, Data Science, sometimes also Applied Math for improving Radiotherapy of Cancer Patients

Interested in deep interactive learning, active learning, semantic/instance segmentation, object detection, interpretability, image manipulation detection. Working with both 2D and 3D data.

My research focus is developing Machine Learning and Computer Vision methods that are tailored towards Remote Sensing and Earth Observation. I have a special interest in Deep Learning (in particular weakly-, semi-, and self-supervised learning) and Ensemble Learning (in particular …

Head of the Helmholtz Imaging Support Unit at DESY Hamburg. Background in computational structural biology, pattern recognition, artificial intelligence, convolutional neural networks and cloud computing.

Interested in everything that is computer vision, regardless of domain

Considering human interaction when designing machine learning (ML) systems bears great potential: On the one hand, decision-making in ML systems remains imperfect in practice, thus requiring human interaction for safety-critical applications such as clinical diagnostics. On the other hand, the …

Part of the Applied Computer Vision Lab (ACVL) at dkfz, Heidelberg. Background in computer vision, deep learning, pattern recognition, 3d reconstruction and variational methods.

I am a deep learning researcher with experience in:
- Self Supervised Learning
- Active Learning
- Supervised Learning
- Generative modeling

For:
- Representation learning
- Denoising
- Resolution enhancement
- Classification
- Semantic segmentation
- Instance segmentation

Applied …

Machine Learning/Data Engineer

My current focus is on applying active learning to reduce the effort needed in labeling Sentinel-2 satellite images. I am experimenting with contrasting learning and uncertainty measurements within deep neural networks.

Research Engineer in Data Science. I have experience in Data processing in Computer Tomography for Material Science and medical Magnetic Resonance Imaging. I am enthusiastic about Machine Learning and Medical Engineering.

Currently working as a Post-Doc researcher at the Forschungszentrum Jülich, conducting research on 3D reconstruction, image segmentation and depth estimation. Working with 2D and 3D data.