V
Vipin Kumar
Researcher at University of Minnesota
Publications - 678
Citations - 67181
Vipin Kumar is an academic researcher from University of Minnesota. The author has contributed to research in topics: Parallel algorithm & Computer science. The author has an hindex of 95, co-authored 614 publications receiving 59034 citations. Previous affiliations of Vipin Kumar include University of Maryland, College Park & United States Department of the Army.
Papers
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Journal ArticleDOI
Application of An Ontology for Characterizing Data Quality For a Secondary Use of EHR Data.
TL;DR: Automating the data quality assessment process using this method can enable sharing of data quality metrics that may aid in making research results that use EHR data more transparent and reproducible.
Proceedings ArticleDOI
A Parameter-Free Spatio-Temporal Pattern Mining Model to Catalog Global Ocean Dynamics
TL;DR: This paper introduces a parameter-free pattern mining application that is able to identify dynamic anomalies in ocean data, known as ocean eddies, and provides one of the first quantitative analyses of the performance of the most used monitoring algorithms.
Proceedings ArticleDOI
Association analysis-based transformations for protein interaction networks: a function prediction case study
TL;DR: Experimental evaluation on several protein interaction data sets show that hyperclique-based transformations enhance the performance of standard function prediction algorithms significantly, and thus have merit.
Posted Content
Research and Education in Computational Science and Engineering
Ulrich Rüde,Karen Willcox,Lois Curfman McInnes,Hans De Sterck,George Biros,Hans Bungartz,James Corones,Evin Cramer,James Crowley,Omar Ghattas,Max D. Gunzburger,Michael Hanke,Robert W. Harrison,Michael A. Heroux,Jan S. Hesthaven,Peter Jimack,Chris R. Johnson,Kirk E. Jordan,David E. Keyes,Rolf Krause,Vipin Kumar,Stefan Mayer,Juan Meza,Knut Martin Mørken,J. Tinsley Oden,Linda R. Petzold,Padma Raghavan,Suzanne M. Shontz,Anne E. Trefethen,Peter R. Turner,Vladimir Voevodin,Barbara Wohlmuth,Carol S. Woodward +32 more
TL;DR: The field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce as discussed by the authors.
Data Mining for the Discovery of Ocean Climate Indices
TL;DR: The use of data mining to discover Ocean Climate Indices (OCIs) is described and a shared nearest neighbor (SNN) clustering algorithm is applied to cluster the pressure and temperature time series associated with points on the ocean, yielding clusters that represent ocean regions with relatively homogeneous behavior.