Bei Wang

Postdoctoral Research Associate

Scientific Computing and Imaging Institute
University of Utah
Warnock Engineering Building (WEB) Room 4660
72 South Central Campus Drive
Salt Lake City, Utah 84112

Email: beiwang AT sci.utah.edu

Office Phone: (801) 585-3911

About

I am a postdoc working with Valerio Pascucci at the Scientific Computing and Imaging (SCI) Institute at the University of Utah. I did my Ph.D. in Computer Science at Duke University with Herbert Edelsbrunner. I also obtained a certificate in Computational Biology and Bioinformatics. During the fall semester of 2009, I was at the Institute of Science and Technology Austria (IST Austria).

Research Interests

Design and analysis of algorithms, data structure, specifically but not limited to: algorithms in computational geometry and topology; algorithms in computational biology and bioinformatics; algorithms in data management. Molecular modeling and simulation.

Extra

I am always open to discussions on topology, geometry, biology, food, and everything in between.

Recent Publications

Towards Stratification Learning through Homology Inference.
Paul Bendich, Sayan Mukherjee, Bei Wang.
Accepted, AAAI 2010 Fall Symposium on Manifold Learning and its Applications, 2010.
PDF Separating Features from Noise with Persistence and Statistics.
Bei Wang.
Ph.D. Thesis, Duke University, 2010.
PDF Computing Elevation Maxima by Searching the Gauss Sphere.
Bei Wang, Herbert Edelsbrunner, Dmitriy Morozov.
Proceedings of the 13th International Symposium on Experimental Algorithms, 2009. Lecture Notes in Computer Science, 5526, pages 281-292, 2009.
PDF A Computational Screen for Site Selective A-to-I Editing Detects Novel Sites in Neuron Specific Hu Proteins.
Mats Ensterö, Örjan Åkerborg, Daniel Lundin, Bei Wang, Terrence S Furey, Marie Öhman and Jens Lagergren.
BMC Bioinformatics, 11(6), 2010.
PDFSpatial Scan Statistics for Graph Clustering.
Bei Wang, Jeff M. Phillips, Robert Schrieber, Dennis Wilkinson, Nina Mishra and Robert Tarjan.
Proceedings of 8th SIAM Intenational Conference on Data Mining, 2008.
PDFA Framework for Modeling DNA Based Molecular Systems.
Sudheer Sahu, Bei Wang and John H. Reif.
Lecture Notes in Computer Science, 4287, pages 250-265, 2006.
PDFTwo Proteins for the Price of One: The Design of Maximally Compressed Coding Sequences.
Bei Wang, Dimitris Papamichail, Steffen Mueller and Steven Skiena.
Proceedings of the 11th International Meeting on DNA Based Computers, 2005. Lecture Notes in Computer Science, 3892, pages 387-398, 2006. Also in Natural Computing, 2006.
PDFExperimental Robot Musicians.
Tarek M. Sobh, Bei Wang and Kurt W. Coble.
Journal of Intelligent and Robotic System, 38(2), pages 197-212, 2003.