Dr. Meyer-Baese has graduated with a PhD in 1995 in Electrical and Computer Engineering from Darmstadt University of Technology, Germany, and has obtained in 2002 the “venia legendi” in Computer Science and Applied Mathematics and published the first monograph in “Pattern Recognition in Medical Imaging”. She is a professor on sabbatical in Scientific Computing at the Florida State University.

She has a very strong interdisciplinary background covering computer science and engineering, computational radiology, computational neuroscience, biomedical engineering, and scientific computing. Her research in the last 30 years has spanned the development of theoretical methods in machine learning such as learning in graphical models, dynamical and temporal graph networks, biosignal processing, Artificial Intelligence, and applications of these methods in medical imaging such as dementia, cancer research and bioinformatics. She has conducted nationally funded research (NSF, NIH) and internationally (European Commission) consistently throughout her career. She has published four books in her primary research area and over two hundred fifty peer-reviewed publications. In recognition of her research, she has received many international and national research recognitions.

Professor Meyer-Baese was the Chair of the 2010 IEEE International Workshop “Database    Technology for Life Sciences and Medicine”, the Chair of several SPIE Conferences in Computational Intelligence and the Program Chair for the SPIE Systems Biology Award. She was and is on the Program Committee on many major conferences in Artificial Neural Networks, Complex Networks, and Computational Biology and she was the Associate Editor of Neural Processing Letters. She served as the Editor in Chief on many Special Issues such as “Modern Control Mechanisms Applied to the Prediction and Evolution of Neurodegenerative Diseases” (Frontiers in Computational Neuroscience), “Advanced graph theoretical approaches in neuroimaging of neurodegenerative disorders” (Frontiers in Computational Neuroscience),  “Artificial Intelligence in Oncology” (Cancers), “Advanced Computer Vision Approaches in Biomedical Image Analysis “, “Advances in Artificial Neural Systems with Applications in Biomedicine and Bioinformatics “ and “Stability Analysis including Mono-stability and Multi-stability in Dynamical Systems and Applications” and as a Guest Editor for Medical Physics.   

Professor Meyer-Baese’s theoretical work in the field of neurodynamics has yielded several breakthrough results, and her research has also contributed to a new direction in the entire field.  She introduced the novel concept of stability analysis based on singular perturbations and different time scales for capturing the aspects of long- and short-term memory in neural networks.          

In parallel, Prof. Meyer-Baese discovered the potential of computational intelligence as a key design element for integrated systems in biomedicine.  In the following, she set up the framework for applying theoretical tools from artificial intelligence to biomedical image processing and worked interdisciplinary with the Lee-Moffitt-Cancer Center in breast cancer research, and with the world-famous MD Anderson Cancer Center and the National High Magnetic Field Laboratory in brain cancer research. She pioneered the application of linear and nonlinear cluster-based independent component analysis methods to the vast area of magnetic resonance imaging including fMRI (functional magnetic resonance imaging), perfusion MRI and breast MRI.

Complementarily, dynamic connectivity models for the understanding of disease evolution and the different state changes representative for various neurodegenerative diseases such as AD have been a core research subject in Meyer-Baese's group. Her research prompted a new view of cognitive control mechanisms that can be described by the control theory in engineering. Meyer-Baese’s group has a substantial experience in dynamical brain networks. She pioneered the concept of finding driver nodes in dementia networks and enhanced current understanding of progressive abnormal neural circuits in many neurodegenerative diseases. The understanding of complex dynamical neural networks in the brain has been a core research subject in Meyer-Baese's group. The group's research is based on understanding the biological properties, but it includes the theoretical analysis, numerical modeling and simulation. Dr. Meyer-Baese has a vast expertise in advanced control mechanisms applied to dynamic graph networks representing complex large-scale dynamical systems in the brain that capture the interaction of a large number of subsystems.

Her unique expertise and research results in bioengineering are documented by her three research monographs “Pattern Recognition for Medical Imaging” published by the very prestigious medical publisher Elsevier Science in 2003 and “Advanced Biomedical Signal Analysis: Contemporary Methods and Applications” in 2010 with MIT Press. Her first monograph was so successful that the Elsevier Press asked her to provide a new completely revised edition “Pattern Recognition and Signal Analysis in Medical Imaging” published in 2013.