Information visualization techniques can be combined with classical and modern data analysis, such as statistical pattern recognition and machine learning, to yield a more powerful, user-controlled information retrieval. The visual feedback guiding the analytical mining process exploits the unmatched capability of the low-level and high-level human visual system to recognize patterns and derive abstract conclusions from them, possibly setting off another analysis round. We are currently exploiting this relatively new paradigm for volume segmentation and for the analysis/classification of large, high-dimensional data streams. We are also working towards a comprehensive visual data mining environment for neuroscientists, called BrainMiner, that will enable a more targeted and experiential derivation of brain functional models from large collections of knowledge and data. The study of more effective and intuitive user interfaces is an important aspect of this work, as well as developing and evaluating these systems in close relationship with domain scientists and end users. For this, we have numerous collaborations at Brookhaven National Laboratory and at Pacific Northwest National Laboratory.

	A High-Dimensional Feature Clustering Approach to Support Knowledge-Assisted Visualization (KAV) J. Nam, M. Maurer, K. Mueller Computers & Graphics (to appear), 2009
	Iconizer: A Framework to Identify and Create Effective Representations for Visual Information Encodings S. Garg, T. Berg, K. Muellerr IEEE Visualization Conference (poster session) Atlantic City, NJ, October, 2009
	Model-Driven Visual Analytics S. Garg, E. Nam, IV. Ramakrishnan, K. Mueller IEEE Symposium on Visual Analytics Science and Technology 2008 (VAST '08) Columbus, OH, October, 2008 pp. 19-26
	Illustrative Parallel Coordinates K. McDonnell and Klaus Mueller Computer Graphics Forum (Special Issue Eurovis '08) vol. 27, no. 3, pp. 1031-1038, 2008.
	ClusterSculptor: A Visual Analytics tool for high-dimensional data E. Nam, Y. Han, K. Mueller, A. Zelenyuk, and D. Imre IEEE Symposium on Visual Analytics Science and Technology 2007 (VAST '07) Sacramento, CA, October, 2007 pp. 75-82
	Toward a Multi-Analyst, Collaborative Framework for Visual Analytics Framework S. Brennan, K. Mueller, G. Zelinsky, IV Ramakrishnan, D. Warren, and A. Kaufman IEEE Symposium on Visual Analytics Science and Technology 2006 Baltimore, MD, October, 2006 pp. 129-136
	SpectraMiner, an Interactive Data Mining and Visualization Software for Single Particle Mass Spectroscopy: A Laboratory Test Case A. Zelenyuk, D. Imre, Y. Cai, K. Mueller, Y. Han, and P. Imrich International Journal of Mass Spectrometry no. 258, pp. 58-73, 2006
	Interactive Poster: 3D ThemeRiver P. Imrich, K. Mueller, D. Imre, A. Zelenyuk, and W. Zhu IEEE Information Visualization Symposium '03 Seattle, October 2003
	Interactive Poster: A Hardware-Accelerated Rubbersheet Focus + Context Technique for Radial Dendrograms   P. Imrich, K. Mueller, D. Imre, A. Zelenyuk, and W. Zhu IEEE Information Visualization Symposium '03 Seattle, October 2003
	Interactive Poster: Visual datamining with the interactive dendogram  P. Imrich, K. Mueller, D. Imre, A. Zelenyuk, and W. Zhu IEEE Information Visualization Symposium '02  Boston, October 2002
	Changes in brain-functional homogeneity in subjects with Alzheimer's disease N. Volkow, W. Zhu, C. Felder, K. Mueller, T. Welsh, G.-J. Wang, and M. de Leon Journal of Psychiatry Research: Neuroimaging vol. 114, no. 1, pp. 39-50, 2002
	Graphical strategies to convey functional relationships in the human brain: A case study T. Welsh, K. Mueller, W. Zhu, N. Volkow, and J. Meade IEEE Visualization '01 San Diego, October 2001 pp. 481-485
	BrainMiner: A visualization tool for ROI-based discovery of functional relationships in the human brain K. Mueller, T. Welsh, W. Zhu, J. Meade, and N. Volkow New Paradigms in Information Visualization and Manipulation (NPIVM) 2000 Washington DC, November 2000
	A medical workstation for the display and analysis of multi-frame digital cineradiographic data K. Mueller, E.L. LaPresto, K.A. Powell, J.L. Hirsch, and J.F. Cornhill Computers in Medicine and Biology vol. 26, no. 5, pp. 385-400, 1996