Reading and discussion group:  Data science in understanding and addressing climate change 

By | Educational, Events, General Interest, Happenings

CSCAR announces a reading and discussion group Data science in understanding and addressing climate change that will meet on the third or fourth (depending on the preferences of participants) Friday of every month between 3 and 5 pm. We will discuss reports and significant papers that illuminate fundamental issues in climate change science, policy, and management. The suggested format at this stage is that we discuss one science and one policy (or management) paper or chapter. The focus will be on the spatial (and temporal) dimensions of the issue and we will concentrate more on methods and techniques keeping the requirement for domain knowledge relatively low. We will lay emphasis on the conceptual part of the tools and techniques so that it is accessible to a wider set of participants, but will also get into the technical details.

This is an effort to bring people involved in climate change together from a data science perspective. The idea is to learn together in a fun environment and foster dialogue with a focus on how data science can provide the common ground for mutual learning and understanding.

 We will meet in Rackham, but we will be open to rotating the location. You will be able to participate remotely, if you choose to.

 If you are interested send an email to Manish Verma at

 If you have any suggestion for discussion and reading let us know.  We will include chapters from the IPCC and US global change science programs in our discussion.

U-M partners with Cavium on Big Data computing platform

By | Feature, General Interest, Happenings, HPC, News

A new partnership between the University of Michigan and Cavium Inc., a San Jose-based provider of semiconductor products, will create a powerful new Big Data computing cluster available to all U-M researchers.

The $3.5 million ThunderX computing cluster will enable U-M researchers to, for example, process massive amounts of data generated by remote sensors in distributed manufacturing environments, or by test fleets of automated and connected vehicles.

The cluster will run the Hortonworks Data Platform providing Spark, Hadoop MapReduce and other tools for large-scale data processing.

“U-M scientists are conducting groundbreaking research in Big Data already, in areas like connected and automated transportation, learning analytics, precision medicine and social science. This partnership with Cavium will accelerate the pace of data-driven research and opening up new avenues of inquiry,” said Eric Michielssen, U-M associate vice president for advanced research computing and the Louise Ganiard Johnson Professor of Engineering in the Department of Electrical Engineering and Computer Science.

“I know from experience that U-M researchers are capable of amazing discoveries. Cavium is honored to help break new ground in Big Data research at one of the top universities in the world,” said Cavium founder and CEO Syed Ali, who received a master of science in electrical engineering from U-M in 1981.

Cavium Inc. is a leading provider of semiconductor products that enable secure and intelligent processing for enterprise, data center, wired and wireless networking. The new U-M system will use dual socket servers powered by Cavium’s ThunderX ARMv8-A workload optimized processors.

The ThunderX product family is Cavium’s 64-bit ARMv8-A server processor for next generation Data Center and Cloud applications, and features high performance custom cores, single and dual socket configurations, high memory bandwidth and large memory capacity.

Alec Gallimore, the Robert J. Vlasic Dean of Engineering at U-M, said the Cavium partnership represents a milestone in the development of the College of Engineering and the university.

“It is clear that the ability to rapidly gain insights into vast amounts of data is key to the next wave of engineering and science breakthroughs. Without a doubt, the Cavium platform will allow our faculty and researchers to harness the power of Big Data, both in the classroom and in their research,” said Gallimore, who is also the Richard F. and Eleanor A. Towner Professor, an Arthur F. Thurnau Professor, and a professor both of aerospace engineering and of applied physics.

Along with applications in fields like manufacturing and transportation, the platform will enable researchers in the social, health and information sciences to more easily mine large, structured and unstructured datasets. This will eventually allow, for example, researchers to discover correlations between health outcomes and disease outbreaks with information derived from socioeconomic, geospatial and environmental data streams.

U-M and Cavium chose to run the cluster on Hortonworks Data Platform, which is based on open source Apache Hadoop. The ThunderX cluster will deliver high performance computer services for the Hadoop analytics and, ultimately, a total of three petabytes of storage space.

“Hortonworks is excited to be a part of forward-leading research at the University of Michigan exploring low-powered, high-performance computing,” said Nadeem Asghar, vice president and global head of technical alliances at Hortonworks. “We see this as a great opportunity to further expand the platform and segment enablement for Hortonworks and the ARM community.”

MDST – NFL Free Agency Value Prediction Competition Kick-Off – Nov. 9, 6pm

By | Data, Data sets, Educational, Events, Happenings, MDSTPosts, MDSTProjects, News

In this competition, student teams at the University of Michigan will use historical free agent data to predict the value of new contracts signed in the 2018 free agency period. These predictions will be evaluated against the actual contracts as they are signed. This competition is organized by the Michigan Data Science Team (MDST), in collaboration with the Baltimore Ravens and the Michigan Sports Analytics Society (MSAS).  Food will be provided. This is an initial kick-off meeting of the competition.


Date, Time

Thursday, November 9 at 6:00 PM EST to Thursday, November 9 at 7:00 PM EST
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Weiser Hall 10th Floor Auditorium
500 Church St, 48104, MI


Michigan Data Science Team



Info session: Consulting and computing resources for data science — Nov. 8

By | Data, Educational, Events, General Interest, Happenings, HPC

Advanced Research Computing at U-M (ARC) will host an information session for graduate students in all disciplines who are interested in new computing and data science resources and services available to U-M researchers.

Brief presentations from members of ARC Technology Services (ARC-TS) on computing infrastructure, and from Consulting for Statistics, Computing, and Analytics Research (CSCAR) on statistics, data science, and computing training and consulting will be followed by a Q&A session, and opportunities to interact individually with ARC and CSCAR staff.

ARC and CSCAR are interested in connecting with graduate students whose research would benefit from customized or innovative computational or analytic approaches, and can provide guidance for students aiming to do this. ARC and CSCAR are also interested in developing training and documentation materials for a diverse range of application areas, and would welcome input from student researchers on opportunities to tailor our training offerings to new areas.


  • Kerby Shedden, Director, CSCAR
  • Brock Palen, Director, ARC-TS


Wednesday, Nov. 8, 2017, 2 – 4 p.m., West Conference Room, 4th Floor, Rackham Building (915 E. Washington St.)

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University of Michigan researcher contributes to NASA findings on carbon in the atmosphere showcased in the journal Science

By | General Interest, Happenings, News


High-resolution satellite data from NASA’s Orbiting Carbon Observatory-2 are revealing the subtle ways that carbon links everything on Earth – the ocean, land, atmosphere, terrestrial ecosystems and human activities. Scientists using the first 2 1/2 years of OCO-2 data have published a special collection of five papers today in the journal Science that demonstrates the breadth of this research. In addition to showing how drought and heat in tropical forests affected global carbon dioxide levels during the 2015-16 El Niño, other results from these papers focus on ocean carbon release and absorption, urban emissions and a new way to study photosynthesis. A final paper by OCO-2 Deputy Project Scientist Annmarie Eldering of NASA’s Jet Propulsion Laboratory in Pasadena, California, and colleagues gives an overview of the state of OCO-2 science.

Manish Verma, a Geospatial/Data Science Consultant at the University of Michigan’s Consulting for Statistics, Computing and Analytics Research (CSCAR) unit, contributed as a coauthor to an article on a new way to measure photosynthesis over time and space.

Using data from the OCO-2, Verma’s analysis helped expand the utility of measurements of solar induced fluorescence (SIF), which indicates active photosynthesis in plants. Verma’s work showed that SIF data collected from the OCO-2 satellite provides reliable information on the variability of photosynthesis at a much smaller scale — down to individual ecosystems.

This can, in turn, “lead to more reliable estimates of carbon sources — that is, when, where, why and how carbon is exchanged between land and atmosphere — as well as a deeper understanding of carbon-climate feedbacks,” according to the Science article.

For more, see the NASA press release ( and the Science article (

Real estate dataset available to researchers

By | Data, Data sets, Educational, General Interest, Happenings, News

The University of Michigan Library system and the Data Acquisition for Data Sciences program (DADS) of the U-M Data Science Initiative (DSI) have recently joined forces to license a major data resource capturing parcel-level information about the property market in the United States.  

The data were licensed from the Corelogic corporation, who have assimilated deed, tax and foreclosure information on nearly all properties in the entire US. Coverage dates vary by county, some county records go back fifty years. Coverage is more comprehensive from the 1990s to the present.

These data will support a variety of research efforts into regional economies, economic disparities, trends in land-use, housing market dynamics, and urban ecology, among many other areas.

The data are available on the Turbo Research Storage system for users of the U-M High Performance Computing infrastructure, and via the University of Michigan Library.

To access the data, researchers must first sign a MOU; contact Senior Associate Librarian Catherine Morse for more information, or visit

U-M, SJTU research teams share $1 million for data science projects

By | Data, General Interest, Happenings, News, Research

Five research teams from the University of Michigan and Shanghai Jiao Tong University in China are sharing $1 million to study data science and its impact on air quality, galaxy clusters, lightweight metals, financial trading and renewable energy.

Since 2009, the two universities have collaborated on a number of research projects that address challenges and opportunities in energy, biomedicine, nanotechnology and data science.

In the latest round of annual grants, the winning projects focus on data science and how it can be applied to chemistry and physics of the universe, as well as finance and economics.

For more, read the University Record article.

For descriptions of the research projects, see the MIDAS/SJTU partnership page.

Liza Levina, PhD, Chosen IMS Medallion Lecturer in 2019

By | Events, Feature, General Interest, Happenings, News, Research

Professor Liza Levina has been selected to present an Institute of Mathematical Statistics (IMS) Medallion Lecture at the 2019 Joint Statistical Meeting (JSM).

Each year eight Medallion Lecturers are chosen from across all areas of statistics and probability by the IMS Committee on Special Lectures. The Medallion nomination is an honor and an acknowledgment of a significant research contribution to one or more areas of research. Each Medallion Lecturer will receive a Medallion in a brief ceremony preceding the lecture.