Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.
Amadeus Gebauer is a Researcher at the Chair of Computational Mechanics within the Institute for Computational Mechanics at the Technical University of Munich (TUM), serving as a Research Associate since 2019. His work specializes in computational biomechanics with emphasis on cardiac mechanics modeling, growth and remodeling processes, and multi-physics simulation frameworks. Education: Master of Science (M.Sc.) in Mechanical Engineering, Technical University of Munich, 2019 Research Interests: Gebauer's research centers on cardiac mechanics modeling, including growth and remodeling of cardiac tissue, cardiac active tissue mechanics, and medical image processing. He develops advanced computational methods for parallel and high performance computing, particularly through the 4C multi-physics simulation framework. His work integrates constrained mixture models to simulate organ-scale biological processes, bridging computational mechanics with clinical cardiology applications and focusing on mechanobiological stability in cardiac systems. Publication Trends: Gebauer's publications (2018-2025) demonstrate consistent innovation in computational cardiology, primarily using constrained mixture models to address cardiac growth and remodeling. His recent work introduces adaptive integration techniques for history variables and homogenized modeling approaches, while expanding into software benchmarking for cardiac elastodynamics and gastric motility simulations. These contributions highlight his expertise in developing robust numerical methods for multi-physics biomedical problems, with increasing focus on patient-specific applications and high-performance computing solutions. Teaching and Advising: Gebauer teaches core computational mechanics courses including Finite Elemente and Numerische Festkörpermechanik across multiple semesters. He has supervised diverse student projects ranging from term papers to Master's theses, with notable collaborations including Maximilian Grill's shoulder biomechanics research (2020) and Janina Datz's artery geometry framework development (2021). His advising consistently focuses on cardiac mechanics, computational modeling, and medical device simulation. Research Environment: As part of Professor Wolfgang A. Wall's Institute for Computational Mechanics (LNM) at TUM, Gebauer contributes to a leading research group in computational solid/fluid mechanics. The LNM develops the 4C simulation framework for complex engineering and biomedical challenges, with current emphasis on cardiac growth modeling, multi-physics integration, and high-performance computing applications in personalized medicine.
Rainer Haag is a Professor at the Department of Chemistry, Freie Universität Berlin, leading the Haag Group in the Institute of Chemistry and Biochemistry. His research focuses on biodegradable and sustainable materials, dynamic hydrogels, and polymeric nanosystems for biomedical applications. Department of Chemistry, Freie Universität Berlin Member of SFB 1449: Dynamic Hydrogels at Biointerfaces Collaborator in the StemGel startup project Co-founder of CSR|Berlin interdisciplinary research institute Research Interests: Development of stimuli-responsive polymers, multivalent virus inhibitors, and functional biointerfaces. Key projects include: Antiviral coatings using heteromultivalent polymers Thermoresponsive hydrogels for stem cell expansion Graphene derivatives for bacterial capture and disinfection Lignin upcycling for sustainable resin materials Supramolecular nanosystems for drug delivery Publication Trends highlight interdisciplinary work in polymer chemistry, nanotechnology, and biomedical applications. Recent articles focus on: 2D polyglycerols for virus interactions Redox-responsive nanogels Mucus-inspired adhesive hydrogels Tumor-targeting micelles Bacterial disinfection using graphene composites Labs & Collaborations include the Polymeric and Supramolecular Nanosystems subgroup, the Dynamic Hydrogels and Biointerfaces team, and partnerships with MIT in developing bioinspired adhesives. His group contributes to DFG-funded SFB 1449 and CSR|Berlin initiatives.
Francesca De Benetti is a Researcher at the Chair of Computer Aided Medical Procedures (Prof. Navab) at the Technical University of Munich (TUM), affiliated with the Interdisciplinary Research Laboratory (IFL) and NARVIS Lab at the Garching Campus. Her research focuses on Nuclear Medicine and Machine Learning for medical image processing, particularly in internal radiation therapy simulations and AI-driven segmentation. Education : M.Sc. in Biomedical Computing (TUM, 2018-2020), B.Sc. in Information Engineering (Università di Padova, 2015-2018) Francesca's recent publications highlight her work in Monte Carlo dosimetry , dynamic PET tracer modeling , and deep learning-based anomaly detection in medical imaging. Her projects emphasize personalized radiation therapy and cross-modality image translation , often involving collaborations with nuclear medicine experts and radiologists. She contributes to teaching at TUM, leading lectures and practical courses on topics including Medical Augmented Reality , Computer Aided Medical Procedures , and Deep Learning for Medical Applications . Francesca is actively involved in labs such as the IFL Lab and NARVIS Lab , focusing on interdisciplinary applications of computer vision and generative AI in medicine.
Prof. Karen Alim is a Professor of Biological Physics and Morphogenesis at the Department of Physics, Technische Universität München (TUM), affiliated with the TUM School of Natural Sciences. She holds a PhD from the Ludwig-Maximilians-Universität München (2010) and conducted postdoctoral research at Harvard University (2010–2015) before leading a Max Planck Research Group in Göttingen. Her research focuses on non-neuronal information processing in living systems, particularly using Physarum polycephalum to study physical principles of network adaptation, fluid dynamics, and morphogenesis. Education: PhD in Physics, Ludwig-Maximilians-Universität München (2010) Studies at Universität Karlsruhe, LMU München, and University of Manchester Research Interests: Prof. Alim explores how biological systems process information without neurons, emphasizing adaptive flow networks, mechanical signaling in plants, and collective behavior in active matter. Her work combines theoretical modeling with experimental systems like slime molds and plant tissues. Awards: ERC Starting Grant (2020) Elisabeth-Schiemann-Kolleg Fellowship (2013–2018) DAAD Stipendium (2011–2014) John Birks Award (2004) Advising & Grants: While specific grant details beyond the ERC award are not listed, her research has been supported by major funding bodies. No student advisees are explicitly listed in the provided materials. Labs/Teams: Leads the Biological Physics and Morphogenesis group at TUM, focusing on interdisciplinary studies of living systems' physical principles.
Prof. Vasilis Ntziachristos is a Professor and Chair of Biological Imaging at the Technical University of Munich (TUM), leading the Institute of Biological and Medical Imaging at the Helmholtz Centre Munich. His research focuses on developing novel optical and optoacoustic imaging techniques for early disease detection, diagnostics, and theranostics. He holds a PhD in Bioengineering from the University of Pennsylvania and previously served as an Assistant Professor at Harvard University and Massachusetts General Hospital. Affiliations: TUM School of Medicine and Health, Helmholtz Munich, Institute of Biological and Medical Imaging. Key Research Themes: Non-invasive imaging methods, molecular imaging, optoacoustic technology, and clinical translation. His work bridges theoretical developments with clinical applications, including advancements in glucose monitoring, cancer imaging, and drug delivery systems. Notable awards include the Leibniz Prize (2013) and the World Molecular Imaging Society Gold Medal (2015). Labs/Teams: Imaging to Sensing I2S, Optoacoustic Mesoscopy, Fluorescence Imaging, and AI in Optoacoustics. Grants/Projects: Involvement in Horizon Europe initiatives and collaborations with TranslaTUM and Helmholtz Munich. Prof. Ntziachristos actively contributes to education via courses like 'Biological Imaging' and 'Introduction to Bioengineering', fostering the next generation of imaging scientists.
Professor Matthias Mann is a world-leading scientist serving as Director of the Proteomics and Signal Transduction department at the Max Planck Institute of Biochemistry in Martinsried, Germany, and Director of the Proteomics department at the Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Denmark. With an h-index exceeding 277 and over 350,000 citations, he is recognized as the highest cited German researcher and one of the most influential scientists globally in proteomics. His educational background includes: Ph.D. in Chemical Engineering from Yale University (1988) Master's Degree in Physics from Georg August University Göttingen (1984) Bachelor's of Arts in Mathematics from Georg August University Göttingen (1982) Professor Mann's research focuses on advancing mass spectrometry-based proteomics to understand biological systems at the protein level. His work spans technological developments in mass spectrometry, bioinformatics and computational analysis, signal transduction and posttranslational modifications, and clinical proteomics applications for disease diagnosis and treatment. The Mann lab has pioneered groundbreaking methods like SILAC for quantitative proteomics and MaxQuant for proteome data analysis. Their vision is to translate proteomics knowledge into clinical practice for predictive, diagnostic, and preventive medicine, with recent work focusing on AI-guided platforms for analyzing proteomes from minimal tissue samples. Analysis of Professor Mann's recent publications reveals a strong trend toward clinical applications of proteomics, particularly in cancer research, metabolic diseases, and neurodegenerative disorders. His work increasingly integrates spatial proteomics, single-cell resolution techniques, and artificial intelligence approaches to uncover disease mechanisms and identify potential biomarkers, with a clear shift from basic technology development toward direct clinical applications and personalized medicine. Professor Mann has received numerous prestigious awards throughout his career: 2025: Elected member of the American National Academy of Sciences 2024: Dr. H.P. Heineken Award for Biochemistry and Biophysics 2023: Otto Warburg Medal 2019: Nominated member of the Bavarian Academy of Sciences 2013: Elected member of Leopoldina German National Academy of Sciences 2012: Körber European Science Award, Louis-Jeantet Foundation Prize for Medicine, Ernst Schering Prize, and Leibniz Prize Professor Mann leads a highly collaborative research team involved in multiple international networks including the Bill & Melinda Gates Foundation, Michael J. Fox Foundation for Parkinson's Research, CLINSPECT-M, and Munich Heart Alliance. His lab has mentored numerous successful researchers, with several former postdocs receiving prestigious ERC Starting Grants. The Mann group has developed innovative clinical proteomics pipelines for analyzing archived tissue specimens and body fluids, aiming to identify protein markers for early detection of diseases such as diabetes and cancer. The Mann lab operates across two major research centers with state-of-the-art mass spectrometry facilities. Their Clinical Knowledge Graph platform integrates multi-omics data with extensive metadata, creating an ecosystem for machine learning applications in proteomics. Current research focuses on developing highly sensitive methods that can profile thousands of proteins from minimal cell samples, enabling the identification of critical disease-related proteins and supporting the development of individualized therapies.
Rhenish Friedrich Wilhelm University of BonnGermany
Prof. Waldemar Kolanus leads the Molecular Immunology and Cell Biology department at the University of Bonn's Life & Medical Sciences Institute (LIMES) . His research bridges immunoregulation , stem cell dynamics , and metabolic stress responses in immune cells. Unit 2 member at LIMES Principal investigator in SFB 704 and ImmunoSensation Cluster Leads a multidisciplinary lab with postdocs, PhD students, and technical staff His work focuses on intracellular signaling pathways connecting immune activation to tissue homeostasis, particularly through: Cytohesin proteins in integrin-mediated adhesion and migration TRIM71 in stem cell regulation and congenital hydrocephalus High-salt environments affecting macrophage function Publication trends show expertise in immune cell migration , genetic models , and chemical inhibition , with frequent use of mice and zebrafish for in vivo studies. Key articles explore: TRIM71's dual role in auditory development and germ cell maintenance Cytohesin family's Golgi regulation and insulin signaling Ruxolitinib's off-target migration inhibition of dendritic cells Contact details: Address: LIMES Institute, Carl-Troll-Straße 31, Bonn Email: kolanus.sekretariat@uni-bonn.de Phone: +49 228 73-62788
Christine Selhuber-Unkel is a Full Professor (W3) for Molecular Systems Engineering at the Institute for Molecular Systems Engineering and Advanced Materials (IMSEAM) at Heidelberg University. She serves as co-chair of the Executive Board of the Flagship Initiative 'Engineering Molecular Systems' and is a spokesperson for the 'Cellular Biophysics' section of the German Biophysical Society. Additionally, she is a member of the executive board of the Cluster of Excellence '3D Matter Made to Order'. Education: Studied physics at Heidelberg University (2000-2002) M.Sc. degree in Physics from Uppsala University (2003) PhD in Physics from Heidelberg University (biological adhesion on nanopatterned substrates) Professor Selhuber-Unkel's research focuses on functional interfaces and their interactions with biological systems, including responsive interfaces, micro-/nanostructured interfaces (including 2-photon laser printing), and biofunctionalized hydrogels. Her work specifically targets controlling cellular properties such as parasite migration, with potential applications in soft robotics and biomaterials. She also experimentally studies biophysical properties of cells including mechanosensing, cellular force generation, adhesion forces, and statistical properties of intracellular motion and migration. Her research group is involved in multiple projects related to parasite physics, including studies on Giardia adhesion, Plasmodium infected erythrocytes, and Toxoplasma gondii. Her recent publications demonstrate a strong focus on hydrogel engineering, cellular mechanics, and microfluidic systems for studying cell behavior. The research spans from fundamental biomaterials development to applications in ophthalmology, tissue engineering, and parasite mechanics. Scientific Awards: European Research Council Consolidator Grant (PHOTOMECH) European Research Council Starting Grant (CELLINSPIRED) Feodor Lynen Fellow for research stay at Cornell University Emmy Noether postdoctoral fellowship Otto Hahn Medal from the Max Planck Society Professor Selhuber-Unkel has received significant research funding, including multiple ERC grants and DFG funding. She previously served as spokesperson for the DFG research training group 'Materials for Brain' at Kiel University (2017-2020). Her research group maintains strong collaborations across multiple institutions focused on biophysical approaches to understanding cellular and parasite mechanics. Her laboratory develops advanced techniques including traction force microscopy, atomic force microscopy (AFM), and microengineered systems for studying cellular mechanics in confined environments. The group's work bridges materials science, biophysics, and parasitology to develop novel approaches for understanding and controlling cellular behavior.
Konstantinos Anastassiadis is a Professor at the Center for Molecular and Cellular Bioengineering (CMCB) of Dresden University of Technology , leading the Stem Cell Engineering group at the Biotechnology Center (BIOTEC) . His research focuses on unraveling molecular pathways regulating stem cell self-renewal and lineage commitment, with a strong emphasis on genetic engineering tool development and epigenetic mechanisms during cellular reprogramming. The lab utilizes mouse and human embryonic stem cells, neural stem cells, mesenchymal stromal cells, and induced pluripotent stem cells (iPSCs) in their investigations. Core Research Areas: Molecular regulation of stem cell fate Epigenetic mechanisms (e.g., UTX/UTY histone demethylases) Genetic engineering tool development (Flp, Dre, Vika recombinases, CRISPR protocols) Conditional immortalization systems for rare cell expansion Publications highlight his contributions to understanding: Role of histone methyltransferases (MLL1, MLL2, Setd1b) in hematopoiesis and cancer Epigenetic regulation during mouse development and spermatogenesis Genetic tools for protein tagging, transposon-mediated BAC transgenesis Interactions between stem cells and niche microenvironments Transcriptional and mechanical markers during reprogramming Collaborations span immunology , developmental biology , and bioinformatics . The lab actively participates in teaching activities at CMCB and maintains a focus on translational applications of stem cell research.
Prof. Dr. Simon Schäfer leads the Schäfer Lab at the Technische Universität München , focusing on engineering advanced organoid systems to study human brain development, disease modeling, and repair mechanisms. His work bridges stem cell biology, gene editing, and bioengineering to develop personalized therapies for brain disorders. Stem Cell & Organoid Technology Neurodevelopmental Mechanisms Neurodegenerative Disease Models Gene Editing & Neuroimmune Interactions Translational Neuroscience Recent research emphasizes brain organoid development, microglia phenotypes, and neurodevelopmental timing anomalies in autism. His team’s work also explores zika virus interactions with glioblastoma stem cells and neuronal plasticity in psychiatric disorders. Scientific awards and funding include support from the Deutsche Forschungsgemeinschaft (DFG), Brain & Behavior Research Foundation (BBRF), and Munich Cluster for Systems Neurology (SyNergy). Collaborations span institutions like the TUM Center for Organoid Systems. Advises 6 students (2 PhD, 1 MSc, 3 associated) Labs include Schäfer Lab, COS@TranslaTUM Contact: simon.schafer@tum.de
Prof. Joachim Spatz is a Full Professor of Biophysical Chemistry at Heidelberg University and Director of the Max Planck Institute for Medical Research. His academic career includes roles as Director at MPI for Metals Research (2004–2015) and Founding Director of the Institute for Molecular Systems Engineering (IMSE). He holds a PhD from Ulm University and habilitation in Physics, with postdoctoral training at the Institut Curie, Paris. His research spans cellular biophysics, materials science, and synthetic biology, focusing on mechanotransduction, cell-material interactions, and engineered biological systems. Education: 1989–1994: Dipl. Phys. (Physics), Ulm University & Colorado State University 1994–1996: PhD (summa cum laude), Ulm University 2000: Habilitation in Physics, Ulm University Research Interests: Spatz’s work integrates biophysics, materials science, and engineering to study cellular mechanics, synthetic cells, and mechanosensing. Key projects include developing synthetic cell models using microfluidics and exploring how mechanical forces regulate cell behavior in health and disease. Awards: 2017 Gottfried Wilhelm Leibniz Prize 2012 ERC Advanced Grant (with Prof. B. Geiger) 2002 Alfried Krupp Research Award Labs & Collaborations: Leads the Cellular Biophysics Department at MPI for Medical Research and collaborates with institutions like the Weizmann Institute and Jackson Laboratory. Active in interdisciplinary initiatives such as the Max Planck School Matter to Life.
Prof. Dr. Martin Kronbichler is a faculty member at the Faculty of Mathematics , Ruhr University Bochum , leading the Numerics group. His research focuses on higher-order finite element methods, multigrid techniques, and high-performance computing for complex fluid and solid mechanics problems. Key Research Areas: Higher-order finite element methods, iterative solvers, multigrid algorithms, exascale mathematical software, and computational fluid dynamics. Notable Projects: EU-funded dealii-X (exascale digital twins), BMBF PDExa (optimized PDE solvers for exascale), and DFG grants for cut-discontinuous Galerkin methods and geometric multigrid. Publications Trends: Recent works emphasize matrix-free operators for hyperelasticity, diffuse-interface models for additive manufacturing, and multigrid smoothers for higher-order elements. Scientific Awards: Recipient of the Humboldt Research Award for his contributions to numerical methods and HPC. Team: Collaborates with researchers like Dr. Shubham Kumar Goswami, Dr. Richard Schussnig, and Natalia Nebulishvili.
Prof. Dr. Stefan Luther is a Max Planck Research Group leader (W2, tenured since 2013) at the Max Planck Institute for Dynamics and Self-Organization, Göttingen, and an Honorarprofessor at the Faculty of Physics, University of Göttingen. He holds adjunct roles as Adjunct Associate Professor at Cornell University (2009–2012) and Northeastern University (2016–2018), and serves as DZHK-Professor at the Institute of Pharmacology and Toxicology, University Medical Center Göttingen. His research focuses on nonlinear spatiotemporal dynamics in excitable biological media, particularly cardiac arrhythmias. He pioneered 4D imaging of heart function and developed algorithms for optogenetic and electrical control of arrhythmias. Translational efforts span basic research to preclinical and clinical studies. Education includes a Diplom in Physics (1997) and PhD (2000) from Georg-August-University, Göttingen. Postdoctoral training followed at the University of Twente (2001–2004) and Cornell University’s LASSP (2004–2006). His lab, the Biomedical Physics group, explores electromechanical coupling in cardiac systems and develops novel therapeutic approaches. Collaborations include work on computational modeling, uncertainty quantification in dynamical systems, and fluid dynamics of multiphase flows.
Nasir M. Rajpoot is a Professor in the Department of Computer Science at the University of Warwick, UK. His research focuses on computational pathology, medical image analysis, and deep learning applications in histology. He leads interdisciplinary projects integrating artificial intelligence with healthcare, particularly in cancer diagnostics and pathology workflows. Rajpoot’s work emphasizes developing robust algorithms for histology image analysis, including nuclear segmentation, tumor classification, and domain generalization in computational pathology. His contributions include the TIAToolbox, an open-source framework for tissue image analytics, and the CoNIC Challenge to advance nuclear detection and counting in histology images. He collaborates with clinicians and biologists to translate AI models into clinical practice, addressing challenges like tumor heterogeneity and staining variability. Rajpoot’s research spans colorectal, lung, and oral cancers, with a focus on predicting clinical outcomes via histological features and genomic data integration. Notable projects include the development of Handcrafted Histological Transformer (H2T) for unsupervised representations of whole slide images and the SAFRON framework for histology image synthesis. His work addresses domain adaptation, robustness evaluation, and explainability in AI-driven pathology systems.
