Labs

The Perioperative Data Science Lab at the Medical University of Vienna (Kimberger Group), develops and validates AI models for perioperative decision support and risk prediction, and investigates the translation of AI methods into perioperative workflows.

We use AI & ML to study disease mechanisms in cellular systems. Specifically, we improve algorithms to make better use existing knowledge in molecular biology to facilitate interpretation and prediction of high throughput measurements, such as single-cell omics

Empowering radiation oncology with AI-driven solutions to deliver safer, more adaptive, and personalized therapies.

The Heilemann group develops advanced machine- and deep-learning methods to automate and optimize key components of radiation therapy

 

We advance AI with quantum computing to build simpler, and highly-generalizable clinical AI models focusing on methods including novel spatial neural networks, quantum neural networks and quantum learning

The Competence Center Artificial Intelligence focuses on the development and application of cutting-edge artificial intelligence tools tailored towards dental applications.

The Dynamics of Neural Systems Laboratory seeks to characterise the dynamical processes underpinning neural computations in the brain, reverse-engineer them in artificial neural networks and derive algorithmic principles shared by these fundamentally different systems.

CTN Lab uses biophysically-constrained ML to address functional and medically-relevant questions in pancreatic islet sensory function.

The interdisciplinary CIR lab is developing novel machine learning methods to predict disease course and treatment response, to inform our understanding of biological processes by connecting real-life imaging data with other modalities. 

The lab led by Christoph Bock at the AI Institute of the Medical University of Vienna combines research in machine learning and bioinformatics with high-throughput biology and applications in cancer and immunology.

ELIA focuses on developing novel technologies to represent, analyse and understand perinatal imaging data from the fetal period until 18 years. Methodologies are tailored to age related dynamics and specifically address developmental changes and interaction with pathologic progression patterns

The High Field MR Center is an interdisciplinary platform for development and clinical translation of Magnetic resonance imaging techniques covering expertise in MR physics, mathematics, biochemistry, machine learning, and biomedical engineering. Our researchers collaborate with various medical disciplines including in particular the sub disciplines of radiology

The MANO group led by Philipp Seeböck develops machine learning methods for anomaly detection in medical imaging, with a focus on data efficiency, integration of medical knowledge, and explainability. As part of CIR, our vision is to enable adaptive and trustworthy AI systems that support both clinical practice and scientific discovery.

The scientific directions of MSBP Group led by Diana Mechtcheriakova are systems biology and systems medicine as part of the global concept of personalized medicine with focus on lymphoid structures and germinal center biology

The NeuroEngLab lead by Stanisa Raspopovic The group uses cutting-edge technology grounded in computational neuroscience to restore lost neurological function. We rebuild the bridge between body, mind, and self.

 

Romanov’s group investigates brain cellular heterogeneity, leveraging machine learning approaches to analyze single-cell sequencing and spatial transcriptomics data. Their work focuses on uncovering spatial coding principles in the brain, with emphasis on both neuronal and glial cell types.

The lab is dedicated to advancing the machine/deep learning methods for medical image analysis in order to advance personalized medicine and propel clinical research

The research group led by Matthias Samwald at the AI Institute of the Medical University of Vienna investigates how highly capable, language-based AI systems can advance precision medicine.

The SHS Lab led by Philipp Aichinger is an engineering research group conducting clinically oriented basic research in the areas of human speech production and hearing. The group focuses on optical imaging and acoustical signals.

The group headed by Stefanie Widder uses computational modeling, ML and network science to investigate how interactions among microbes and the immune system drive emergent pathologies.