Current Membership in Professional Organizations




НазваниеCurrent Membership in Professional Organizations
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Curriculum Vitae


Anke Meyer-Baese


August 20, 2012


General Information


University address: Scientific Computing
College of Arts & Sciences
Dirac Library 0400
Florida State University
Tallahassee, Florida 32306-4120

E-mail address: ameyerbaese@fsu.edu


Professional Preparation


1995 Ph.D., Darmstadt University of Technology. Major: Electrical and Computer Engineering. Computational neuroscience. Supervisor: Wolfgang Hilberg. Magna cum laude.


Postdegree Education and Training


1995–1996 Postdoctoral fellow with the Federal Institute of Neurobiology, Magdeburg, Germany.


Professional Credential(s)


2002–present Habilitation (Venia legendi).


Professional Experience


2008–present Associate Professor, Scientific Computing, Florida State University.


2006–2008 Associate Professor, Electrical and Computer Engineering, Florida State University.


2001–2006 Assistant Professor, Electrical and Computer Engineering, Florida State University.


Visiting Professorship(s)


2009 European Molecular Biology Organization.


2002–2003 Department of Mathematics and Computer Science, Kassel University, Germany.


1996–2001 Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL.


1996–2001 Department of Electrical Engineering, Technical University of Darmstadt, Germany.


Honors, Awards, and Prizes


EMBO, European Molecular Biology Organization Award (2009).

College of Engineering Research Award, FAMU/FSU College of Engineering (2006).

NIH Research Career Award, NIH (2005).

Humboldt Foundation Research Award, Alexander v. Humboldt Foundation (2004).

WISC Award, American Advancement of Sciences (2003).

Lise-Meitner-Prize, Federal State of Germany (1997).

Mildred-Scheel Cancer Research Award, Mildred Scheel Cancer Foundation (1997).

Max-Kade Research Award for Neuroengineering, German National Research Foundation (1996).


Current Membership in Professional Organizations


Institute of Electrical and Electronic Engineers


Teaching


Courses Taught


Data Mining (ISC5935)

Hardware Digital Signal Processing (EEL4930)

Adaptive Neural Systems (EEL5930)

Algorithms for Neural Networks (EEL4930)

Electrical Engineering Senior Design (EEL4911L)

Digital Signal Processing I (EEL6502)

Digital Signal Processing (EEL4510)

Introduction to Communications (EEL3512)

Statistical Topics in Electrical Engineering (EEL4021)


New Course Development


Data Mining (2009)

Algorithms for Neural Networks (2007)

Adaptive Neural Systems (2007)

Advanced Neural Networks (2005)

Digital Signal Processing (2001)


Curriculum Development


Computational methods for discrete problems (SC Undergraduate Curriculum) (2009)

Curriculum design for undergraduate degree in Computational Science (2009)

Curriculum development for Computer Vision and Machine Learning Program for Center for Intelligent Systems, Control, and Robotics (CISCOR) (2002)


Doctoral Committee Chair


Ejaz, M., graduate. (2008). A framework for implementing Independent Component Analysis algorithms (Electrical and Computer Engineering).


Isaacs, J., graduate. (2007). Kernel methods and component analysis for pattern recognition (Electrical and Computer Engineering).


Saalbach, A., graduate. (2006). Exploratory Analysis of Multivariate Image Data (Electrical and Computer Engineering).


Twellmann, T., graduate. (2005). Data-Driven Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Data in Breast Cancer Diagnosis (Electrical and Computer Engineering).


Skinner, D. E., doctoral candidate. (2011).


Perry, M., doctoral student. (2012).


Zavala, O., doctoral student. (2012).


Doctoral Committee Cochair


Joshi Shantanu, graduate. (2007). Shape Analysis for Computer Vision. Graduate Research and Creativity Award. (Electrical and Computer Engineering).


Ding, L., doctoral candidate. (2013). Scientific Computing.


Lay, N., doctoral candidate. (2012). Scientific Computing.


Doctoral Committee Member


Hoang, H. H., graduate. (2010).

Xu, X., graduate. (2009).

Yu, H. G., graduate. (2007).

Du Pont, E., graduate. (2007).

Davis, W., graduate. (2006).

Jastrzembski, T., graduate. (2006).

Liu, X., graduate. (2006).

Wang, Y., graduate. (2005).

Cruz-White, I., graduate. (2003).

Siddiqui, S. A., doctoral candidate.

Yu, H., doctoral candidate.


Doctoral Committee University Representative


Langoni, D., doctoral candidate.

Yu, H., doctoral candidate.

Perry, W., doctoral student. (2012).


Master's Committee Chair


Moses, T., graduate. (2008). A Survey of Antennas for Wireless Communication Systems.


Steinbruecker, F., graduate. (2008). Tumor Classification on Breast MR Images.


Chandrasekhar, N., graduate. (2005). Optimization of a Parallel Cordic Architecture to Compute the Gaussian Potential Function in Neural networks.


Sanchez, B., graduate. (2005). Speaker Identification Based on an Integrated System Combining Cepstral Feature Extraction and Vector Quantization.


Thomas Dan Otto, graduate. (2002). Application of Model-Free Methods in fMRI Data Analysis.


Master's Committee Cochair


Lay, N., graduate. (2009). Supervised Aggregation of Classifiers using Artificial Prediction Markets.


Master's Committee Member


Aaron, R. C., graduate. (2010).

Powell, N., graduate. (2008).

Liu, L., graduate. (2008).

Chanila, M., graduate. (2006).

Thierren, D., graduate. (2006).

Langoni, D., graduate. (2005).

Chaganti, V., graduate. (2005).

Chiari, Y., graduate. (2005).

Rajagopalan, V., graduate. (2005).

Sunkara, D. L., graduate. (2004).

Yu, H. G., graduate. (2004).

Cordes, B., graduate. (2003).

DuPont, E., graduate. (2003).

Dukes, K., graduate. (2003).

Hogans, T., graduate. (2003).

Rao, S., graduate. (2003).

Siddiqui, S., graduate. (2003).

Sripathi, D., graduate. (2003).

Akali, M., graduate. (2002).


Additional Teaching Not Reported Elsewhere


Plant, C. (2010). Postdoctoral Fellow. FSU.


Saalbach, A. (2007). Postdoctoral Fellow. FSU.


Meyer-Baese, A. (2007). Senior Design Project: Radio Frequency Robot. Department of Electrical and Computer Engineering, FSU.


Meyer-Baese, A. (2006). Senior Design Project: Using Spectral Subtraction to Enhance Speech and Improve Performance in Automatic Speech Recognition. Department of Electrical and Computer Engineering, FSU.


Thuemmler, V. (2006). Postdoctoral Fellow. FSU.


Twellmann, T. (2006). Postdoctoral Fellow. FSU.


Theis, F. (2004). Postdoctoral Fellow. FSU.


Lange, O. (2003). Postdoctoral Fellow. FSU.


Research and Original Creative Work


Program of Research and/or Focus of Original Creative Work


My research is based on the development and application of novel exploratory data analysis methods and nonlinear analysis techniques to medical imaging, bioinformatics and systems biology.


Publications


Invited Journal Articles


Meyer-Baese, A., Koshkouei, A., Emmett, M., & Goodall, D. (2009). Global Stability Analysis and Robust Design of Multi-Time-Scale Biological Networks Under Parametric Uncertainties. Neural Networks, 658-663.


Meyer-Baese, A., Schlossbauer, T., Lange, O., & Wismueller, A. (2009). Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI. international Journal of Biomedical Imaging, 326924, 10. Retrieved from http://www.hindawi.com/journals/ijbi/2009/326924.html


Lange, O., Meyer-Baese, A., Hurdal, M., & Foo, S. (2006). A Comparison Between Neural and Fuzzy Cluster Analysis Techniques for functional MRI. Biomedical Signal Processing and Control, 1, 243-252.


Meyer-Baese, A., Hurdal, M., & Lange, O. (2005). Clustering of Dependent Components: A New Paradigm for fMRI Signal Detection. Applied Signal Processing, 19, 3089-3102.


Meyer-Baese, A., Meyer-Baese, U., Watzel, R., & Foo, S. (2003). A Parallel CORDIC Architecture to Compute the Gaussian Potential Function in Neural Networks. Engineering Applications of Artificial Intelligence, 16, 595-605.


Foo, S., Stuart, G., Harvey, B., & Meyer-Baese, A. (2002). Neural Network Based EKG Pattern Recognition. Engineering Application of Artificial Intelligence, 15, 252-260.


Meyer-Baese, A. (1999). On the Existence and Stability of Solutions in Self-Organizing Cortical Maps. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E82-A9, 1883-1887.


Refereed Journal Articles


Althaus, E., Canzar, C., Ehrler, C., Emmett, M., Karrenbauer, A., Marshall, A., Meyer-Baese, A., Tipton, J., & Zhang, H.-M. (in press). Computing H/D-Exchange Rates of Single Amino Acid Residues from LC MS data. BMC Bioinformatics, 18 pages.


Meyer-Baese, A., Roberts, R., & Thuemmler, V. (2010). Local Uniform Stability of Competitive Neural Networks with Different Time-Scales under Vanishing Perturbations. Neurocomputing, 73, 770-775.


Meyer-Baese, U., Vera, A., Meyer-Baese, A., Pattichis, M., & Perry, R. (2010). An Undergraduate Course and Laboratory in Digital Signal Processing with Field Programmable Gate Arra. IEEE Transactions on Education, 53, 1. Retrieved from http://www.ieeexplore.ieee.org.proxy.lib.fsu.edu/stamp/stamp.jsp?tp=&arnumber=5393015


Gruber, P., Meyer-Baese, A., Foo, S., & Theis, F. (2009). ICA, Kernel Methods and Nonnegativity: New Paradigms for Dynamical Component Analysis for fMRI Data. Engineering Applications of Artificial Intelligence, 22, 497-504.


Saalbach, A., Meyer-Baese, A., Lange, O., & Nattkemper, T. (2009). On the Application of (Topographic) Independent and Tree-Dependent Component Analysis for the Examination of DCE-MRI Data. Biomedical Signal Processing and Control, 4, 247-253.


Meyer-Baese, A., & Thuemmler, V. (2008). Local and Global Stability Analysis of an Unsupervised Competitive Neural Network. IEEE Transactions on Neural Networks, 19, 346-351.


Schlossbauer, T., Leinsinger, G., Wismueller, A., Lange, O., Meyer-Baese, A., & Reiser, M. (2008). Classification of small contrast enhancing breast lesions in dynamic magnetic resonance imaging using a combination of morphological criteria and dynamic analysis based on unsupervised vector-quantiza. Investigative Radiology, 43, 56-64.


Twellmann, T., Meyer-Baese, A., Lange, O., Foo, S., & Nattkemper, T. (2008). Model-free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning. Engineering Applications of Artificial Intelligence, 21, 129-140.


Meyer-Baese, A., Lange, O., Wismueller, A., & Hurdal, M. K. (2007). Analysis of dynamic susceptibility contrast MRI time series based on unsupervised clustering methods. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 11, 563-573.


Meyer-Baese, A., Roberts, R., & Yu, H. (2007). Robust Stability Analysis of Competitive Neural Networks with Different Time-Scales Under Perturbations. Neurocomputing, 71, 417-420.


Meyer-Baese, A., Saalbach, A., Lange, O., & Wismueller, A. (2007). Unsupervised Clustering of fMRI and MRI Time-Series. Biomedical Signal Processing and Control, 2, 295-310.


Meyer-Baese, A., Gruber, P., Theis, F., & Foo, S. (2006). Blind Source Separation Based On Self-Organizing Neural Network. Engineering Application of Artificial Intelligence, 19, 305-311.


Meyer-Baese, A., & Pilyugin, S. (2006). Stability Analysis of an Unsupervised Neural Network with Feedforward and Feedback Dynamics. Neurocomputing, 70, 603-606.


Wismueller, A., Meyer-Baese, A., Lange, O., Kallergi, M., Leinsinger, G., & Reiser, M. (2006). Segmentation and Classification of Dynamic Breast MR Image Data. Optical Engineering, 15, 013020.


Wismueller, A., Meyer-Baese, A., Lange, O., Reiser, M., & Leinsinger, G. (2006). Cluster Analysis of Dynamic Cerebral Contrast—Enhanced Perfusion MRI Time-Series. IEEE Transactions on Medical Imaging, 25, 62-73.


Meyer-Baese, A., Jancke, K., Wissmueller, A., Foo, S., & Martinetz, T. (2005). Medical Image Compression Using Topology-Preserving Neural Networks. Engineering Application of Artificial Intelligence, 18, 383-392.


Meyer-Baese, A., Jancke, K., Wismueller, A., & Georgiopoulos, M. (2004). Fast k-dimensional Tree-Structured Vector Quantization Encoding Method for Image Compression. Optical Engineering Letters, 43, 1012-1013.


Meyer-Baese, A., Pilyugin, S., Wismueller, A., & Foo, S. (2004). Local Exponential Stability of Competitive Neural Networks with Different Time-Scales. Engineering Applications of Artificial Intelligence, 16, 227-232.


Meyer-Baese, A., Wismueller, A., & Lange, O. (2004). Comparison of Two Exploratory Data Analysis Methods for fMRI: Unsupervised Clustering versus Independent Component Analysis. Transactions on Information Technology in Biomedicine, 8, 387-398.


Meyer-Baese, A., Wissmueller, A., Lange, O., & Ritter, H. (2004). Model-free functional MRI Analysis Using Topographic Independent Component Analysis. International Journal of Neural Systems, 14, 217-229.


Wismueller, A., Meyer-Baese, A., Lange, O., Auer, D., Reiser, M., & Sumners, D. (2004). Model-free functional MRI Analysis Based on Unsupervised Clustering. Biomedical Informatics, 37, 10-18.


Wismueller, A., Vietze, F., Behrends, J., Meyer-Baese, A., Reiser, M., & Ritter, H. (2004). Fully-Automated Biomedical Image Segmentation by Self-Organized Model Adaptation. Neural Networks, 17, 1327-1344.


Meyer-Baese, A., & Piljugin, S. (2003). Global Asymptotic Stability of a Class of Dynamical Neural Networks. International Journal of Neural Systems, 13, 47-53.


Meyer-Baese, A., Pilyugin, S., & Chen, Y. (2003). Global Exponential Stability of Competitive Nueral Networks with Different Time-Scales. IEEE Transactions on Neural Networks, 14, 716-719.


Meyer-Baese, U., Meyer-Baese, A., & Scheich, H. (2000). An Interspike Interval Method to Compute Speech Signals from Neural Firing. Biological Cybernetics, 82, 283-290.


Meyer-Baese, A. (1999). Hyperstability Conditions for Hopfield-Type Neural Networks. Int. Journal of Neural Systems, 9, 95-99.


Meyer-Baese, A., & Watzel, R. (1998). Transformation Radial Basis Neural Network for Relevant Feature Selection. Pattern Recognition Letters, 12, 11301-1306.


Meyer-Baese, U., Meyer-Baese, A., Mellott, J., & Taylor, F. (1998). A Fast Modified CORDIC-Implementation of Radial Basis Neural Networks. ". Journal of VLSI SIGNAL PROCESSING SYSTEMS for Signal, Image and Video Technology, 9, 290-298.


Meyer-Baese, A. (1997). Analysis of a Class of Noise Perturbed Neural Networks. International Journal on Neural Systems, 6, 295-301.


Meyer-Baese, A. (1997). Hardware Implementations of Radial Basis Neural Networks. Frequenz, 2, 50-55.


Meyer-Baese, A., Ohl, F., & Scheich, H. (1996). Singular Perturbation Analysis of Competitive Neural Networks with Different Time-Scales. Neural Computation, 8, 545-563.

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