The KEMAI Team

Associated Researchers

Meet the associated researchers of the KEMAI project team.

11 researchers
Alicia Pirwass, M.Sc.
Alicia Pirwass, M.Sc.
Institute of Artificial Intelligence
Explanation of classification decisions for medical hybrid systems
Daniel Wolf, M.Sc.
Daniel Wolf, M.Sc.
Institute for Media Informatics, Visual Computing Group
Deep Learning for Medical Imaging
Dennis Eisermann, M.Sc.
Dennis Eisermann, M.Sc.
Institute of Distributed Systems
Defending Autonomous Systems with Explainable AI Against Adversarial Threats
Hannah Kniesel, M.Sc.
Hannah Kniesel, M.Sc.
Institute for Media Informatics, Visual Computing Group
Neural representation learning for bio-medical image processing
MH
Marietta Hamberger, M.Sc.
Institute of Medical Systems Biology, Ulm University
Regulatory inference under uncertainty: mechanistic and functional abstractions in systems biology
PS
Patricia Stöhr, M.Sc.
Institute of Media Informatics, Ulm University
Explainable Medical AI
PK
Paul Kaftan, M.Sc.
Institute of Medical Systems Biology, Ulm University
Robust and Explainable Deep Learning for Clinical Decision Support
Poonam, M.Sc.
Poonam, M.Sc.
Institute for Media Informatics, Visual Computing Group
The role of representation learning in deep learning
SJ
Saloni Giteshkumar Jethwa, M.Sc.
Visual Computing Group, Ulm University
Precision Movement Analysis and Brain Mapping
Veronika Stiegler, M.Sc.
Veronika Stiegler, M.Sc.
Comprehensive Cancer Center Ulm (CCCU)
ONCO-INSIGHT - Integrated Oncogenomic Insights for Tumor Board Discussions
Alicia Pirwass, M.Sc.
Alicia Pirwass, M.Sc.
Institute of Artificial Intelligence
Explanation of classification decisions for medical hybrid systems
Daniel Wolf, M.Sc.
Daniel Wolf, M.Sc.
Institute for Media Informatics, Visual Computing Group
Deep Learning for Medical Imaging
Dennis Eisermann, M.Sc.
Dennis Eisermann, M.Sc.
Institute of Distributed Systems
Defending Autonomous Systems with Explainable AI Against Adversarial Threats
Hannah Kniesel, M.Sc.
Hannah Kniesel, M.Sc.
Institute for Media Informatics, Visual Computing Group
Neural representation learning for bio-medical image processing
MH
Marietta Hamberger, M.Sc.
Institute of Medical Systems Biology, Ulm University
Regulatory inference under uncertainty: mechanistic and functional abstractions in systems biology
PS
Patricia Stöhr, M.Sc.
Institute of Media Informatics, Ulm University
Explainable Medical AI
PK
Paul Kaftan, M.Sc.
Institute of Medical Systems Biology, Ulm University
Robust and Explainable Deep Learning for Clinical Decision Support
Poonam, M.Sc.
Poonam, M.Sc.
Institute for Media Informatics, Visual Computing Group
The role of representation learning in deep learning
SJ
Saloni Giteshkumar Jethwa, M.Sc.
Visual Computing Group, Ulm University
Precision Movement Analysis and Brain Mapping
Veronika Stiegler, M.Sc.
Veronika Stiegler, M.Sc.
Comprehensive Cancer Center Ulm (CCCU)
ONCO-INSIGHT - Integrated Oncogenomic Insights for Tumor Board Discussions

Medical Doctoral Researchers

1
VB
Valentina Bainova
Klinik für Nuklearmedizin, Universitätsklinikum Ulm
Comparison of delta-radiomics machine learning with multi-omics and survival analysis using standard imaging parameters in low-risk NSCLC patients prior to primary surgery — with a focus on preoperative FDG PET/CT
VB
Valentina Bainova
Klinik für Nuklearmedizin, Universitätsklinikum Ulm
Comparison of delta-radiomics machine learning with multi-omics and survival analysis using standard imaging parameters in low-risk NSCLC patients prior to primary surgery — with a focus on preoperative FDG PET/CT