Homepage of Attila Gyulassy

Affiliations:
    Institute for Data Analysis and Visualization
    Department of Computer Science
    University of California, Davis

Center for Applied Scientific Computing
Lawrence Livermore National Laboratory

Contact:
Phone (914) 406 - 5731
Email: aggyulassy@ucdavis.edu

Research Interests:
    data analysis, topology-based visualization,
    computational topology, applications of Morse     theory, multi-scale techniques,
    topology-based image segmentation.

Info:
I just finished my studies, at UC Davis, and will begin a post-doc position at University of Utah in January 2009. In the dim recesses of the misty past, I graduated from UC Berkeley with a BA in Applied Mathematics and a BA in Computer Science. I love thinking about theoretical problems, and have had a lot of fun developing new algorithms for topology-based visualization and data analysis. In particular, my research has focused on developing a combinatorial algorithm for finding the Morse-Smale complex for volumetric domains. Over the course of iterations, unexpected surprises, and some serious brain-sweating, we came up with a scalable and efficient algorithm for constructing quasi-Morse-Smale complexes for scalar data of any dimension and any (reasonable) data format. More details will be revealed in my upcoming thesis!

My academic adviser is Bernd Hamann. I have been supported in my studies first by a GANN fellowship, then in the Lawrence Scholar Program with my mentor Valerio Pascucci at Lawrence Livermore National Laboratory. I also have worked closely with Peer-Timo Bremer and Vijay Natarajan, who have helped me immensely.

My hobbies include traveling, hiking, bike touring, skiing, windsurfing, jet skiing, climbing, ultimate, volleyball, soccer, swimming, reading, puzzles, and eating.

Here is a link to my CV.

Publications:

Practical Considerations in Morse-Smale Complex Computation
Attila Gyulassy, Peer-Timo Bremer, Valerio Pascucci, Bernd Hamann.
to appear in TopoInViz 2009

Combinatorial Construction of Morse-Smale Complexes for Data Analysis and Visualization.
Attila Gyulassy, PhD Dissertation, University of California, Davis.

A Practical Approach to Morse Smale Complex Computation: Scalability and Generality.
Attila Gyulassy, Peer-Timo Bremer, Valerio Pascucci, Bernd Hamann:
IEEE Trans. Vis. Comput. Graph. (IEEE Visualization 2008), 14(6): 1619-1626, 2008.

Topologically Clean Distance Fields.
Attila Gyulassy, Mark A. Duchaineau, Vijay Natarajan, Valerio Pascucci, Eduardo Bringa, Andrew Higginbotham, Bernd Hamann:
IEEE Trans. Vis. Comput. Graph. (IEEE Visualization 2007), 13(6): 1432-1439, 2007.

Efficient Computation of Morse-Smale Complexes for Three-dimensional Scalar Functions.
Attila Gyulassy, Vijay Natarajan, Valerio Pascucci, Bernd Hamann:
IEEE Trans. Vis. Comput. Graph. (IEEE Visualization 2007), 13(6): 1440-1447, 2007.

A Topological Approach to Simplification of Three-Dimensional Scalar Functions.
Attila Gyulassy, Vijay Natarajan, Valerio Pascucci, Peer-Timo Bremer, Bernd Hamann
IEEE Trans. Vis. Comput. Graph. (by invitation) 12(4): 474-484 (2006)

Topology-based Simplification for Feature Extraction from 3D Scalar Fields.
Attila Gyulassy, Vijay Natarajan, Valerio Pascucci, Peer-Timo Bremer, Bernd Hamann:
IEEE Visualization (IEEE Visualization 2005), pp 535-542, 2005.