IEEE Pacific Visualization Symposium 2016 Best Paper Award

Paul Rosen, in collaboration with Primoz Skraba (Jozef Stefan Institute), Bei Wang (University of Utah), Guoning Chen (University of Houston), Harsh Bhatia (Lawrence Livermore National Laboratory), and Valerio Pascucci (University of Utah), was awarded the best paper award at the IEEE Pacific Visualization Symposium 2016 for their paper titled, “Critical Point Cancellation in 3D Vector Fields: Robustness and Discussion”.

This IEEE sponsored international visualization symposium is held in the Asia-Pacific region, with the objective to foster greater exchange between visualization researchers and practitioners, and to draw more researchers in the Asia-Pacific region to enter this rapidly growing area of research.

More information on the IEEE Pacific Visualization Symposium can be found here.

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International Conference on Information Visualization Theory and Applications Awards

Paul Rosen and his PhD student from University of Utah, Hoa Nguyen, received two awards at the 2016 International Conference on Information Visualization Theory and Applications.

Paul Rosen and Hoa Nguyen received the Best Paper Award for their publication “Improved Identification of Data Correlations through Correlation Coordinate Plots”. They also received the Best PhD Project Award for “Data Scalable Approach for Identifying Correlation in Large and Multi-dimensional Data”. According to the conference awards page, “Papers receiving these awards were selected from a set of outstanding papers, based on the quantitative and qualitative classifications as well as comments provided by the program committee reviewers, their final classification as full paper and their oral presentation at the conference”.

More information on the awards, as well as previous award winners, can be found here.

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Rosen awarded ALMA Development Project grant from the National Radio Astronomy Observatory

Paul Rosen along with Bei Wang (University of Utah), Chris Johnson (University of Utah), Jeff Kern (NRAO), and Betsy Mills (NRAO) received a 1-year ALMA Development Project grant from the National Radio Astronomy Observatory for $185k. The grant is titled “Feature Extraction and Visualization of AMLA Data Cubes through Topological Data Analysis”.

The project is a feasibility study for applying forms of data analysis and visualization never before tested by the ALMA community. Through contour tree-based Topological Data Analysis, we seek to improve upon existing data cube analysis and visualization. This will come in the form of improved accuracy and speed in finding features, which are robust to noise, and a better visual description of features once identified. We will build prototype software, which creates visualizations that help in characterizing and analyzing the spectra of complex spectral line sources within a given data cube.

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Rosen Receives NSF Award

Paul Rosen along with Bei Wang (University of Utah) received a NSF grant with additional collaborative award for Carlos Scheidegger (University of Arizona) for 4 years totaling $1.03M. The grant is titled “III: Medium: Collaborative Research: Topological Data Analysis for Large Network Visualization.” Rosen’s portion of this grant, to be subcontracted from the University of Utah, is $325K.

This project leverages topological methods to develop a new class of data analysis and visualization techniques to understand the structure of networks. Networks are often used in modeling social, biological and technological systems, and capturing relationships among individuals, businesses, and genomic entities. Understanding such large, complex data sources is highly relevant and important in application areas including brain connectomics, epidemiology, law enforcement, public policy and marketing. The proposed research will be evaluated over multiple data sources, including but not limited to large social, communication and brain network datasets. Furthermore, the new approaches developed in this project will be integrated into growing data analysis curricula, shared through developing workshops, and used as topics to continue attracting underrepresented groups into STEM fields and computer science specifically.

For more information about the award, click here and for more information about the award with amendments, click here.

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