In this video from the Intel HPC Developer Conference, Franz Kiraly from Imperial College London and the Alan Turing Institute describes why many companies and organizations are beginning to scope their potential for applying rigorous quantitative methodology and machine learning.
Data Analytics, Machine Learning, and HPC in Today’s Changing Application Environment
November 15, 2016 by
insideAI News Guide to Scientific Research
December 1, 2015 by
In this new insideAI News Guide to Scientific Research, the goal is to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.
Cornell to Lead Aristotle Cloud Federation for Research
November 3, 2015 by
Today Cornell University announced a five-year, $5 million project sponsored by the National Science Foundation to build a federated cloud comprised of data infrastructure building blocks (DIBBs) designed to support scientists and engineers requiring flexible workflows and analysis tools for large-scale data sets, known as the Aristotle Cloud Federation.
Video: Data-driven Education and the Quantified Student
August 6, 2015 by
In this video from the PyData Seattle Conference, Lorena Barba from George Washington University presents: Data-driven Education and the Quantified Student. “Education has seen the rise of a new trend in the last few years: Learning Analytics. This talk will weave through the complex interacting issues and concerns involving learning analytics, at a high level. The goal is to whet the appetite and motivate reflection on how data scientists can work with educators and learning scientists in this swelling field.”
Primary Motivators of Big Data vis-à-vis Scientific Research
June 25, 2015 by
This article is the second in an editorial series with a goal to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.
DataFest Competition Brings Big Data to College Students
April 29, 2015 by
Students from more than 20 prestigious colleges and universities recently tried their hand at “Big Data” analysis at seven different campuses around the country during DataFest, an annual month-long data-analytics competitive event sponsored by the American Statistics Association.
Statistics is the Fastest Growing Undergraduate STEM Degree
February 7, 2015 by
Statistics—the science of learning from data—is the fastest-growing science, technology, engineering and math (STEM) undergraduate degree in the United States over the last four years, an analysis of federal government education data conducted by the American Statistical Association (ASA) revealed.
The Major Roadblocks Facing the Smart City
November 20, 2014 by
In this special guest feature, Cristian Borcear of NJIT reflects on the evolution of technology and public policy in support of so-called “smart cities. ” Cristian Borcea is an Associate Professor and the Associate Chair of the Department of Computer Science at New Jersey Institute of Technology.
Performance Optimization of Hadoop Using InfiniBand RDMA
October 11, 2014 by
“The Hadoop framework has become the most popular open-source solution for Big Data processing. Traditionally, Hadoop communication calls are implemented over sockets and do not deliver best performance on modern clusters with high-performance interconnects. This talk will examine opportunities and challenges in optimizing performance of Hadoop with Remote DMA (RDMA) support, as available with InfiniBand, RoCE (RDMA over Converged Enhanced Ethernet) and other modern interconnects.”
The userR!2014 Conference in Review
July 7, 2014 by
FIELD REPORT Last week I attended the long-anticipated useR!2014 international conference at the UCLA campus, my alma mater. The four day event had something for everyone in attendance – all the brain cycles centered around the use of the R statistical environment. Since R is a primary tool for my work in data science and […]
