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.
Prof. Dr.-Ing. Lars Linsen is a full Professor of Computer Science at the Westfälische Wilhelms-Universität (WWU) Münster, leading the VISualization & graphIX (VISIX) group. His primary affiliation is the Institute of Computer Science within the Faculty of Mathematics and Computer Science. He holds adjunct professorships at Jacobs University, Bremen, and has held previous academic roles including Full Professor at Jacobs University (2012–2017) and Associate/Assistant Professor roles in Germany and the U.S. His research focuses on interactive visual analysis, medical visualization, and scientific visualization, with applications in life sciences and engineering. Education: PhD (Dr.-Ing.) in Computer Science from Universität Karlsruhe (2001), M.Sc. (Diplom) in Computer Science (1997), B.Sc. (Vordiplom) in Computer Science (1994). Awards: IEEE Visualization Design Contest Winner (2008, 2022, 2018), Preis des Fördervereins des Forschungszentrum Informatik (2002). Research Highlights: Develops visualization tools for medical imaging (e.g., mass spectrometry imaging, MRI data analysis) and physical simulations (e.g., wildfire spread analysis, asteroid impact modeling). Active in EU-funded projects like Pig-Pro-QuO (surface coatings) and cells-in-motion initiatives. Supervised over 20 PhD/MS advisees, including notable graduates in medical visualization and simulation ensemble analysis. Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions on Visualization and Computer Graphics, Computers & Graphics, and EuroVis. Key works include SciVis contest-winning wildfire analysis frameworks and medical visualization tools for stenosis detection. Teaching: Offers courses on visualization, computer graphics, and computational science. Actively involved in thesis supervision and curriculum development at both WWU Münster and Jacobs University. Grants & Collaborations: Principal investigator on DFG-funded projects (e.g., hemodynamics simulations, ensemble visualization) and industry collaborations (e.g., Tascon GmbH for coating quality analysis). Member of the Cells-in-Motion Interfaculty Centre and CDH board at WWU.
Prof. Andreas Bausch holds the Heinz Nixdorf Endowed Chair of Cell Biophysics at the Technical University of Munich (TUM) within the TUM School of Natural Sciences . His research focuses on cellular biophysics , particularly the mechanical properties of cytoskeletal networks and self-organization mechanisms in biological systems, with applications in biomimetic materials and organoid modeling. Research Areas : Cytoskeletal mechanics, active matter systems, organoid morphogenesis, integrin signaling, synthetic cell models Techniques : Microrheology, in vitro reconstitution, microfluidics, advanced imaging His work has produced over 100 publications in Nature, Science, PNAS , and Physical Review Letters , with recent emphasis on pancreatic cancer organoids and artificial cell membranes . Key findings include: Discovery of topological excitations governing endothelial cell ordering Elucidation of PIP2/PIP3 regulation in integrin phase separation Development of 3D patterned organoid systems for drug screening Major awards include: ERC Synergy Grant (2018) ERC Advanced Grant (2012) ERC Starting Grant (2011) Berlin-Brandenburg Academy of Sciences Prize (2014) He serves as founding director of the Center for Functional Protein Assemblies (CPA) since 2015 and teaches biomechanics , biophysics , and protein assemblies at TUM. His lab investigates both fundamental biophysical principles and their medical applications in cancer and cardiovascular systems.
Ralf Zimmer is a Full Professor for Practical Informatics and Bioinformatics at Ludwig Maximilian University of Munich (LMU) since 2001, affiliated with the Department of Informatics in the Faculty of Mathematica, Informatics and Statistics. He concurrently serves as Head of Section III and Head of the Research Group Network Regulation and Modeling / Machine Learning at the Leibniz Institute for Food Systems Biology at TUM (Leibniz-LSB@TUM) in Freising, Germany. His academic foundation includes a Diploma with distinction in Computer Science, Applied Mathematics and Operations Research from the University of Bonn (1981-1986), followed by a summa cum laude Doctorate in Computer Science and Applied Mathematics from CAU Kiel in 1990, where he received dual honors: the CAU Dissertation Award and Best Dissertation Award. Zimmer's research pioneers the integration of bioinformatics, systems biology, and machine learning to decode molecular food-consumer interactions. His group develops causal system models for biological networks, validated through in silico simulations and multi-omics perturbation experiments (transcriptomics/proteomics). Core methodologies include network regulation modeling, algorithmic bioinformatics, and database construction linking food compounds to biochemical networks and cellular phenotypes, with translational goals for food and biotech innovation. His 14 most recent publications (2012-2024) reveal dominant trends in multi-omics immunology and cardiovascular research, featuring computational innovations for high-throughput data analysis. Key themes include host-pathogen dynamics (viral infections), inflammatory disease mechanisms (atherosclerosis), and methodological advances in proteomics/transcriptomics, consistently bridging fundamental bioinformatics with clinical applications. Major scientific recognitions include: CAU Dissertation Award and Best Dissertation Award (1990) Director of LMU's Informatics Department (2010-2012) DFG Review Board membership for biomedical foundations (2008-2016) Leadership of the DFG Bioinformatics Munich Center (2001-2008) Academic Senate election at LMU München (2011) Zimmer directs LMU/TUM's joint B.Sc./M.Sc. bioinformatics programs since 2001 as founding architect of the DFG-funded Bioinformatics Munich initiative. His educational leadership spans spokesperson roles for international training groups (IRTG RECESS), collaborative research centers (SFB1123 Atherosclerosis), and elite programs (Data Science, Munich Center for Machine Learning). Grant stewardship includes directing the DFG Bioinformatics Munich Center and shaping national funding policy via the DFG review board. At Leibniz-LSB@TUM, his research group pioneers databases connecting food compounds to cellular phenotypes through molecular networks, collaborating with Munich universities, clinics, and biotech partners to develop high-throughput sequencing/proteomics applications for future food and health innovations.
Prof. Dr.-Ing. Maria Francesca Spadea serves as Director of the Institute of Biomedical Engineering (IBT) at Karlsruhe Institute of Technology (KIT), part of the Helmholtz Association. Her leadership role includes overseeing research initiatives, teaching activities, and administrative responsibilities within the institute. Located in space 512, she maintains regular consultation hours on Wednesdays from 10:30-11:30 am by appointment. Professor Spadea's research spans several cutting-edge areas in biomedical engineering, with particular focus on medical image processing, artificial intelligence applications in healthcare, and radiomics. Her work bridges computational techniques with clinical applications, emphasizing practical solutions for medical imaging challenges. She has pioneered approaches in federated learning for medical image translation, particularly in CT/MRI synthesis for radiation therapy applications. Her research also extends to cancer cell analysis, vascular biomechanics, and medical robotics, demonstrating a broad yet cohesive research portfolio that addresses critical challenges in modern healthcare. Analysis of Professor Spadea's recent publications reveals a strong emphasis on AI-driven medical imaging solutions, particularly in the translation between different imaging modalities (like MRI-to-CT) using federated learning approaches that preserve patient privacy. Her work demonstrates growing specialization in radiation therapy applications, with multiple publications addressing synthetic CT generation for treatment planning. There's also a clear trajectory toward multi-institutional collaboration, as evidenced by her involvement in projects spanning multiple research centers across Europe. Professor Spadea actively mentors numerous students, including M. Krohmer Zabaleta, N. Skupien, and M. Destito, who have completed bachelor's and master's theses under her supervision. Her research group appears well-integrated within the broader Institute of Biomedical Engineering, collaborating extensively with colleagues like P. Zaffino and C.B. Raggio on multiple projects. The group maintains strong connections with clinical partners, as evidenced by publications addressing real-world medical challenges in radiation therapy, cardiology, and neurosurgery. The research activities of Professor Spadea's team are centered within the Institute of Biomedical Engineering at KIT, with particular focus on medical imaging processing and AI applications. Her laboratory appears to specialize in developing computational tools for medical image analysis, with recent work emphasizing privacy-preserving federated learning frameworks that enable multi-institutional collaboration without sharing sensitive patient data. The team maintains active collaborations with clinical departments, particularly in radiation oncology, as evidenced by numerous publications addressing CT synthesis for radiation therapy planning.
Lorenz Dörschel is an Adjunct Professor (Lehrbeauftragter) at the Institute of Automatic Control at RWTH Aachen University. He holds the academic title PD Dr.-Ing. habil, signifying post-doctoral research qualifications. His position is part-time, focusing on advanced control theory and applications. His primary research interests include: Control of distributed parameter systems (e.g., fluid dynamics, thermal processes) Model predictive control for industrial and automotive systems Parameter space methods for robust controller design Model reduction techniques for complex nonlinear systems Dörschel's recent publications (2018-2024) demonstrate broad applications across biomedical engineering, renewable energy, automotive systems, and industrial automation. His work consistently integrates mathematical rigor with practical implementations, emphasizing advanced control methodologies like nonlinear MPC, Lyapunov-based design, and Bayesian optimization. A recurring theme is the development of computationally efficient control strategies for distributed parameter systems. No scientific awards, student advising relationships, or research grants are documented in the available information.
Claas Wegner is a Professor at Bielefeld University, Germany, where he serves as the Lead Professor of the Osthushenrich Center for Giftedness Research (OZHB) at the Faculty of Biology. He also holds positions at the FHM in Bielefeld (teaching Psychology) and at the University of Koblenz (Biology Didactics). His academic journey includes a doctorate in Biology Didactics and Psychology from Bielefeld University (2009), followed by progressive academic appointments leading to his current professorship since 2015. Wegner's educational background includes comprehensive teacher training for secondary schools with a focus on biology, education, and sports (2000-2006), followed by his trainee teacher period (2007-2008). His academic qualifications were solidified with his doctoral degree in Biology Didactics and Psychology from Bielefeld University in 2009. Professor Wegner's research primarily focuses on biology education and giftedness research, with particular emphasis on: Development and validation of diagnostic instruments for identifying scientifically gifted students Implementation of interdisciplinary teaching approaches, especially connecting biology with physical education Use of technology in science education, including 3D modeling, augmented reality, and simulations Gender-specific approaches in STEM education, particularly for girls Health education, with a focus on basic life support and cardiovascular health Design-Based Research methodology in educational contexts His recent publications demonstrate a strong trend toward integrating emerging technologies like AI and AR into science education while maintaining a focus on giftedness identification and interdisciplinary approaches. Wegner's work increasingly explores how digital tools can enhance traditional biology education and make complex concepts more accessible to students of varying abilities. Professor Wegner leads the Osthushenrich Center for Giftedness Research and directs multiple educational projects including Kolumbus-Kids, ELVIS (Erklärvideos inklusionssensibel gestalten), and various initiatives focused on science education and giftedness. His research team works extensively with school laboratories (teutolab-biology, teutolab-medicine, teutolab-sport) to develop innovative teaching approaches and materials. As an educator, Wegner supervises numerous BA and MA theses, leads project modules, and organizes excursions and workshops. His teaching portfolio includes courses on biology didactics, practical teaching studies, and specialized topics in gifted education. He also serves in various administrative capacities including as Deputy member of the BiSEd Conference and member of the Faculty Conference and Quality Improvement Commission.
Prof. Dr. Jan-David Liebe is a Professor of Digital Society at Osnabrück University of Applied Sciences, leading the Digital Health Management field. He holds a PhD in Business Informatics from the University of Osnabrück (2013–2018). His research focuses on implementation science in healthcare, human-centered design, and AI-driven healthcare innovations. He is a co-founder of innnow GmbH and an associated researcher at UMIT’s Institute for Medical Informatics. Key roles include heading the GMDS AG mwmKIS and contributing to national IT reports in healthcare. Research Interests: His work spans digital transformation in healthcare, evaluating healthcare IT maturity models, and fostering innovation through design thinking. Notable projects include benchmarking health IT systems and developing frameworks for AI-supported diagnostics. Professional Roles: Prof. Liebe serves as the Study Director for the Health Management MA program and Entrepreneurship Officer at the WiSo faculty. He actively contributes to research networks like the German Society for Medical Informatics and advises on healthcare IT strategies. Grants & Projects: Leads projects on cloud readiness of hospitals, VR-based medical training, and AI in echocardiography. His work is published in over 50 peer-reviewed articles, emphasizing practical applications of digital tools in healthcare workflows and policy. Affiliations: Member of the Research Commission and Study Committee at Osnabrück University of Applied Sciences. Collaborates with institutions like the Medical School Hamburg and Novia University of Applied Sciences.
Pramita Bagchi is an Assistant Professor in the Department of Biostatistics & Bioinformatics at The George Washington University (GWU), affiliated with the Milken School of Public Health. She holds a Ph.D. in Statistics from the University of Michigan and completed a postdoctoral fellowship at Ruhr Universitat Bochum in Germany. Her research focuses on developing statistical methodologies for analyzing dependent data, particularly in high-dimensional and functional contexts such as time series, spatial data, and functional observations. Education: Ph.D. in Statistics, University of Michigan, Ann Arbor Postdoctoral Research, Department of Mathematics, Ruhr Universitat Bochum Research Interests: Functional Data Analysis Spatiotemporal Modeling High-Dimensional Data Non-Parametric Inference Healthcare Applications Methodological Development for Biomedical Data Publications span statistical theory (e.g., functional time series analysis) and applied health research (e.g., heart transplant biomarkers, acculturation effects in immigrant health). Recent work emphasizes methodological innovations for complex data structures, blending theoretical rigor with real-world applications in cardiology and epidemiology. Grants & Collaborations: NSF Grant: "Empirical Frequency Band Analysis for Functional Time Series" (2022–2025) INOVA Hospital Grant: "Clinical Data Analytics in Cardiac Transplantation" (2020–2023) Teaching includes advanced courses like Mathematical Statistics I (STAT 872), reflecting her expertise in statistical theory and methodology.
Leonid Goubergrits is a Professor of Cardiovascular Modeling and Simulation at the Einstein Center Digital Future and Charité – Universitätsmedizin Berlin . With a background in applied mathematics and physics from the Moscow Institute of Physics and Technology, he has dedicated his career to applying computational fluid dynamics (CFD) to cardiovascular medicine since immigrating to Germany in 1995. His work bridges fundamental research and clinical applications, aiming to integrate numerical models into everyday medical practice to enhance diagnostics and reduce invasiveness. Doctorate at Technische Universität Berlin (2000) Habilitation at Technische Universität Berlin (2016) His research spans blood flow modeling in coronary vessels, cerebral aneurysms, heart valves, and the aorta, alongside artificial organ development and blood damage modeling . He leads a research group at Charité and the German Heart Center Berlin, focusing on patient-specific simulations and their translation to clinical settings. Recent publications highlight his work on deep learning integration for hemodynamic analysis, 4D Flow MRI validation , and medical device optimization using computational models. His team’s research includes virtual therapy planning for aortic valve replacements, hemolysis modeling , and pulmonary artery pressure sensors . Leonid actively contributes to education, redesigning TU Berlin’s Fluid Mechanics in Medicine curriculum and fostering interdisciplinary collaboration between engineers, physicians, and computer scientists. His vision emphasizes the digital transformation of medicine through computational modeling and simulation.
Michael Neidlin is a Senior Researcher in the Department of Cardiovascular Engineering at the Helmholtz-Institute for Biomedical Engineering , RWTH Aachen University. His work focuses on numerical modeling of biological systems for cardiovascular and cardiopulmonary applications. Current Position: Oberingenieur (Senior Engineer), Modeling & Simulation Research Field (2020–present) Past Positions: Postdoctoral Fellow at National Technical University of Athens and Universitat Pompeu Fabra (2017–2020) Education: Dr. rer. medic. (2013–2016) and M.Sc./B.Sc. in Mechanical Engineering (RWTH Aachen) His research spans continuum biomechanics , systems-level modeling , and data-driven approaches to develop translational models for clinical and industrial applications. He specializes in: Multiscale modeling of cardiovascular hemodynamics In-silico evaluation of ventricular assist devices (LVADs) Computational tools for osteoarthritis drug screening Fluid-structure interaction studies in cardiopulmonary bypass
Dr. Wolfgang Hübner is a Researcher at the Faculty of Physics at University of Bielefeld, Germany, affiliated with the Biomolecular Photonics Group. His work focuses on advanced optical imaging techniques applied to cellular and molecular structures. He maintains an active research program as evidenced by numerous publications from 2023-2025. His research interests center on photonics, biophotonics, optical microscopy, super-resolution imaging techniques, cellular biophysics, and molecular imaging. Dr. Hübner's work bridges physics and biology, developing and applying cutting-edge microscopy methods to address biological questions at the nanoscale level. His recent publications demonstrate a strong focus on super-resolution microscopy techniques, particularly structured illumination microscopy, fluorescence lifetime imaging, and correlative imaging approaches. His research investigates cellular structures like liver sinusoidal endothelial cells, dystroglycan mutants, and mitochondrial dynamics, revealing how advanced optical methods can visualize biological processes at unprecedented resolution. Dr. Hübner's research shows consistent development in both methodological advances in optical imaging and biological applications. His work spans from fundamental optical engineering to biomedical applications, demonstrating interdisciplinary expertise across physics, engineering, and cell biology.
Prof. Dr. med. Volker Harth serves as University Professor of Occupational Medicine and Maritime Medicine at the University Medical Center Hamburg-Eppendorf. With an extensive publication record of 495 works, his research spans occupational health, maritime medicine, public health, and epidemiology, with significant contributions to the German National Cohort (NAKO) study and the Hamburg City Health Study (HCHS). Dr. Harth's research focuses on workplace health hazards, occupational disease prevention, maritime health issues, and the intersection of work conditions with health outcomes. His work examines digital stress in healthcare settings, violence prevention in emergency departments, seafarer health, and lung cancer screening for asbestos-exposed workers. He has made substantial contributions to understanding the relationship between work conditions and various health outcomes including respiratory diseases, cardiovascular conditions, and mental health. His methodological approach combines large cohort studies with qualitative investigations into workplace conditions. Dr. Harth frequently collaborates with interdisciplinary teams across multiple institutions, reflecting the complex nature of occupational and maritime health research. His work bridges clinical medicine, public health policy, and occupational safety regulation, with notable contributions to position papers on implementing national lung cancer screening programs. As an educator, Dr. Harth contributes to medical training in occupational and maritime medicine, developing curricula and training future specialists in these fields. His recent work shows increasing attention to digital health issues and the mental health impacts of the pandemic on healthcare workers and other occupational groups.
Dr. Patrick Vogel is a Habilitation candidate and researcher in the Magnetic Particle Imaging (MPI) group at the University of Würzburg's Faculty of Physics and Astronomy, Department of Experimental Physics V. His work focuses on advancing MPI technology for clinical applications, including imaging safety assessments, interventional procedures, and nanoparticle-based diagnostics. He contributes to the development of portable MPI scanners and hybrid imaging systems, collaborating with the AG Behr research group. His research spans magnetic particle spectroscopy, vascular imaging, and biomaterial characterization. Vogel has pioneered studies on MPI-guided endovascular interventions and the application of MPI in perfusion models. His work bridges physics, biomedical engineering, and clinical practice, with a focus on translating MPI into real-world medical diagnostics and surgery support. Key projects include the design of human-sized MPI scanners, safety evaluations of medical implants, and the use of synthetic tracers like Synomag®. He collaborates with interdisciplinary teams to address challenges in vascular imaging, nanoparticle behavior analysis, and real-time imaging systems.
Dr. Mirko Nitschke is a senior researcher at the Leibniz Institute of Polymer Research Dresden (IPF), affiliated with the Max Bergmann Center of Biomaterials Dresden. He has been instrumental in advancing polymer biomaterials science since joining the institute in 1996, focusing on plasma-based surface engineering and biocompatible material development for medical applications. His academic foundation includes: Graduate studies (1992-1996) at Chemnitz University of Technology, where he investigated FTIR Spectroscopic Investigation of Plasma Modified Polymer Surfaces Physics undergraduate degree (1987-1992) from Friedrich-Schiller-University Jena with thesis on Computer Simulation of Ion Trajectories in Solids Nitschke's research centers on plasma surface functionalization and polymer diagnostics to engineer biocompatible materials. His work bridges fundamental surface science with clinical applications, particularly in vascular stents, nerve regeneration, and corneal tissue engineering. Key innovations include thermo-responsive cell carriers and bioactive hydrogel coatings that respond to physiological cues. Analysis of his 15 most recent publications reveals a strong trajectory in advanced biomaterials characterization using ToF-SIMS and plasma techniques. His work increasingly integrates machine learning for spectral analysis while maintaining focus on medical device applications—particularly in cardiovascular and ophthalmic implants where surface-biology interactions dictate clinical success. As a core member of the Polymer Biomaterials Science Division, Nitschke collaborates extensively with clinical partners through the Max Bergmann Center's university-linked infrastructure. His laboratory specializes in plasma modification systems and surface analytics for next-generation biomaterials development.
