Midwest Big Data Hub Transportation and Mobility Conference, Ann Arbor, MI

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The Midwest Big Data Hub

Conference

 

 

 

 

“Big Data for Transportation and Mobility”

 

Please Register

Details are on the main conference webpage.

 

The NSF supported Midwest Big Data Hub has made data for transportation a priority.  Its goal is to bring together experts in the increasingly powerful tools of Big Data (including visualization, machine learning, statistical models, integration of heterogeneous data, data scrubbing, privacy and security) with domain experts.  The Midwest has been a center of innovation in transportation for generations and data-related research has become a major focus of interest for corporate, academic, and governmental organizations.  This conference includes a series of presentations providing an overview of research underway in the Midwest hat will help us understand the scope of this work, encourage cross-fertilization, and possibly nucleate future collaborations.

One of the highlights of the meeting will be a series of talks by faculty from the schools that are the core of the Midwest Big Data Hub.  Additional activities include tours of research sites on the Ann Arbor Campus, short tutorials and breakout sessions on pertinent topics. 

Students are especially welcome and a poster session, part of the conference reception on June 22, will provide an opportunity for them to share their research. There is some limited travel and hosting funding available for students; restrictions apply and requests for travel/ hosting support should be submitted while registering. 

The Midwest Big Data Hub is supported by the National Science Foundation through award #1550320. 

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MBDH Big Data Seminar Series: Iowa State University, Federal Statistical Research Data Centers: How to Get Involved

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Midwest Big Data Hub

The Iowa State University Big Data Seminar Series

‘Federal Statistical Research Data Centers:

Opportunities and How to Get Involved’

Presenters:

Lily Wang, Associate Professor of Statistics

Florence Honore, Assistant Professor of Management

 Zhengyuan Zhu, Associate Professor of Statistics

 

Federal Statistical Research Data Centers (FSRDCs) are special research facilities where qualified researchers conduct approved statistical analysis on non-public data collected by U.S. Census Bureau and other agencies in the federal statistical system. This presentation will give an introduction of FSRDCs and the exciting opportunities that it can bring to ISU researchers – faculty, research staff, and graduate students.

Register for the event here.

Workshop co-chaired by MIDAS co-director Prof. Hero releases proceedings on inference in big data

By | Al Hero, Educational, General Interest, Research | No Comments

The National Academies Committee on Applied and Theoretical Statistics has released proceedings from its June 2016 workshop titled “Refining the Concept of Scientific Inference When Working with Big Data,” co-chaired by Alfred Hero, MIDAS co-director and the John H Holland Distinguished University Professor of Electrical Engineering and Computer Science.

The report can be downloaded from the National Academies website.

The workshop explored four key issues in scientific inference:

  • Inference about causal discoveries driven by large observational data
  • Inference about discoveries from data on large networks
  • Inference about discoveries based on integration of diverse datasets
  • Inference when regularization is used to simplify fitting of high-dimensional models.

The workshop brought together statisticians, data scientists and domain researchers from different biomedical disciplines in order to identify new methodological developments that hold significant promise, and to highlight potential research areas for the future. It was partially funded by the National Institutes of Health Big Data to Knowledge Program, and the National Science Foundation Division of Mathematical Sciences.

Institute for the Humanities Lecture: Jay Clayton

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Jay Clayton, PhD

William R. Kenan, Jr. Professor of English
Director of the Curb Center for Art, Enterprise, and Public Policy

 

“A Humanist in the World of Genomics:

Privacy, Big Data, and Science Policy”

 

Abstract: How can humanists successfully compete for NIH and NSF funding? What roles can the humanities play in the public sphere? How can we influence public policy around a host of issues ranging from genomics, neuroscience, and medicine to the environment, economic inequality, racial disparities, digital media, and big data? Drawing on his experience as a Co-PI and researcher on two collaborative NIH grants totaling more than $4-million, as director of a center focused on the role of the arts in shaping public policy, and as a participant in projects with the Institute of Medicine, Personal Genome Project, Broad Institute, and several Medical schools, Jay Clayton will outline answers that have worked at his institution and other universities.

Bio: Jay Clayton is author or editor of seven books and more than 35 articles and chapters, and he has received fellowships from the Guggenheim Foundation, the American Council of Learned Societies, and elsewhere. His published scholarship has ranged from Romantic poetry and the Victorian novel to contemporary American literature, film and digital media, science and literature, and medicine, health, and society. His book, Charles Dickens in Cyberspace: The Afterlife of the Nineteenth Century in Postmodern Culture, focused on the depiction of computers, information technology, and cyborgs from the Victorian era to the twenty-first century. This study won the Suzanne M. Glasscock Humanities Prize for Interdisciplinary Scholarship. His recent work has concentrated on the ethical, social, and cultural issues raised by genomics.

Big Data in Finance

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On Thursday and Friday, October 27-28, 2016, the Office of Financial Research and the University of Michigan’s Center on Finance, Law and Policy will host a joint conference, “Big Data in Finance” in Ann Arbor, Michigan. The conference will bring together a wide range of scholars, regulators, policymakers, and practitioners to explore how big data can be used to enhance financial stability and address other challenges in financial markets.

The Big Data in finance conference, which is held in collaboration with the Michigan Institute for Data Science (MIDAS), the Michigan Ross School of Business, the Michigan College of Engineering and Michigan Law School will explore ways to make financial data more accessible and more secure, as well as more useful to regulators, market participants, and the public. As new data sets are created, opportunities emerge. Vast quantities of financial data may help identify emerging risks, enable market participants and regulators to see and better understand financial networks and interconnections, enhance financial stability, bolster consumer protection, and increase access to the underserved. Financial data can also increase transparency in the financial system for market participants, regulators and the public.

Transportation Research Board symposium on transformational technologies — Oct. 31-Nov. 1, Detroit

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The Transportation Research Board (TRB) of the National Academies of Science, Engineering, and Medicine is sponsoring the “Partners in Research Symposium: Transformational Technologies” on October 31-November 1, 2016, in Detroit, Michigan.

Registration is open and Patron opportunities are available.

Additional details can be found under the “Program” tab in the symposium website.

New technologies have the potential to transform transportation as we know it. Public agencies are being challenged to facilitate the deployment of these technologies in a manner and timeframe that will lead to improved safety, reduced congestion, enhanced sustainability, and economic development. This TRB symposium will bring leaders from the public and private sectors and academia together to help generate research and innovations to enable agencies to meet this challenge. The symposium will lay the foundation for research roadmaps and partnerships.

Technologies that are expected to be addressed include connected and automated vehicles, shared-use mobility services, smart cities and the internet-of-things, unmanned aircraft systems, NextGen, big data and cybersecurity, and alternative fueled vehicles.

U-M telecast of XSEDE Big Data workshop

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XSEDE and the Pittsburgh Supercomputing Center are presenting a one day Big Data workshop. This workshop will focus on topics such as Hadoop and Spark. U-M is one of several sites around the country that will host a telecast of the session. Registration is required as space is limited.

Schedule:

11:00 Welcome
11:25 Intro to Big Data
11:45 Hadoop
12:15 Hadoop(continued)
1:00 Lunch break
2:00 Exercises
2:45 Spark
3:45 Exercises
4:15 A Big Big Data Platform
5:00 Adjourn

Ivo Dinov interviewed by NOVA/PBS

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Ivo Dinov was interviewed by NOVA/PBS to discuss a recent PNAS Report identifying significant potential shortfalls of Big Data functional magnetic resonance imaging (fMRI) studies, of which there may be over 35,000 in the past 25 years.

The article used 500 normal control subjects (null data) to generate 3 million simulation studies where every experiment included randomly chosen subjects, either resting state or task activation fMRI, and found false-positive discoveries (significant grouping effects where there were none) in up to 70 percent of the simulations.

Although this does not discredit any specific previously published fMRI findings, the investigations suggests the need for novel Big Data analytics methods, and scalable software tools, that can reduce the false-positive rate.

Digging Into Data Challenge seeks data science projects in social science and humanities — June 29 deadline

By | Funding Opportunities, General Interest, News | No Comments

The Digging Into Data Challenge, which aims to address how “big data” changes the research landscape for the humanities and social sciences, is seeking submissions for its fourth found of funding.

Digging into Data is a grant program sponsored by several leading research funders from around the world (see each round below). Teams of researchers from at least two different participating countries send in grant applications. These applications are reviewed by an international peer review panel.

Examples of the titles of previous grant winners include:

  • Automating Data Extraction from Chinese Texts
  • Digging Archaeology Data: Image Search and Markup
  • Field Mapping: An Archival Protocol for Social Science Research Findings.

For more information on the program, see its website. For information on applying, see the Application Materials page. The deadline is June 29, 2016