February 21 @ 9:30 am - 4:00 pm
Audience: Those who have never used Stata before but wish to learn. By the end of the workshop, participants will be able to: Work with Stata, including using Do-files and…
February 24 @ 3:00 pm - 5:00 pm
Multilevel modeling is the state-of-the-art approach for handling data with complex dependence structure in a regression analysis. This workshop will discuss fitting multilevel models in Python using the Statsmodels package….
February 26 @ 10:00 am - 12:00 pm
In this workshop we will use Make to manage build dependency in a multi-file, multi-language software project. We will learn how to use Make functions, automatically generate dependencies, and inquire…
February 28 @ 1:00 pm - 4:00 pm
This workshop will be heavy on conceptual understanding of basic regression modeling, but with demonstration of activities both essential and tangential to good modeling practice. GLM, model interpretation, model comparison,…
Electricity in India
Many still live in darkness
U-M Assistant Professor of Political Science Brian Min is using the Flux high performance computing cluster to analyze thousands of satellite images showing the output of electric lights in India.
His Nightlights website shows satellite images collected over 20 years from more than 600,000 villages. Min’s research reveals that some local units of government have overstated their progress in electrification, and that political considerations play into which regions get electricity, among other things.
Read the U-M press release for more details.
Sharon Broude Geva elected as chair of CASC
Sharon Broude Geva, the Director of Advanced Research Computing at the University of Michigan, has been elected chair of the Coalition for Academic Scientific Computation (CASC).
Founded in 1989, CASC advocates for the use of advanced computing technology to accelerate scientific discovery for national competitiveness, global security, and economic success. The organization’s members represent 84 institutions of higher education and national labs.
Combining Big Data and HPC
A new way of computing could lead to immediate advances in aerodynamics, climate science, cosmology, materials science and cardiovascular research.
The National Science Foundation will provide $2.42 million to develop a unique facility for refining complex, physics-based computer models with big data techniques at the University of Michigan. The university will provide an additional $1.04 million.
$5 million to widen ‘bottleneck to discovery’
An NSF grant will create a software-defined network between three Michigan universities
Buried in troves of data that scientists have gathered, but not yet analyzed, could be key insights to improving cancer treatment, understanding Alzheimer’s, predicting climate change effects and developing cheaper, clean energy technologies.
Those are just a few of the countless examples of fields where our capacity to gather scientific data now far exceeds our capacity to crunch it—especially when collaborations span the globe. Some research projects are producing the equivalent of 1,000 consumer hard drives a month, for example. Read more.
ARC Symposia and Cyberinfrastructure (CI) Days
ARC’s multidisciplinary research institutes, the Michigan Institute for Data Science (MIDAS) and the Michigan Institute for Computational Discovery and Engineering (MICDE), hold annual symposia bringing together like-minded researchers from across U-M and beyond.
- MIDAS Symposium 2017
- MICDE Symposium 2017
- MIDAS Symposium 2016
- MICDE Symposium 2016
- MIDAS Symposium 2015
- Joint MICDE/MIDAS Symposium 2014
ARC’s predecessor, the Office of Research Cyberinfrastructure or ORCI held annual Cyberinfrastructure (CI) Days events to bring the computational research community together, including prominent speakers and poster competitions: