Gilbert, Rudelson, Wu named Simons Foundation Fellows in Mathematics

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Three University of Michigan professors have been named Simons Fellows in Mathematics by the Simons Foundation:

  • Anna Gilbert, the Herman H. Goldstine Collegiate Professor of Mathematics, core faculty member at the Michigan Institute for Data Science (MIDAS), and Professor of Electrical and Computer Engineering
  • Mark Rudelson, Professor of Mathematics
  • Sijue Wu, Robert W. and Lynn H. Browne Professor of Science and Professor of Mathematics.

Forty fellows were named in all.

The fellowships provide funding that allows faculty to take up to a semester-long research leave from teaching and administrative duties. The foundation also gives fellowships in Theoretical Physics.

For more information, see www.simonsfoundation.org.

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.

Emily Mower Provost Receives NSF CAREER Award to Develop Emotion and Mood Recognition for Mental Health Monitoring and Treatment

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Prof. Emily Mower Provost has been awarded an NSF CAREER grant for her research project, “Automatic Speech-Based Longitudinal Emotion and Mood Recognition for Mental Health Monitoring and Treatment.”

Prof. Mower Provost’s research interests are in human-centered speech and video processing, multimodal interfaces design, and speech-based assistive technology. The goals of her research are motivated by the complexities of human emotion expression and perception.

More information about the project is available from the College of Engineering and Prof. Mower Provost’s CAREER Award Posting by NSF.

Ambuj Tewari selected as 2017 Alfred P. Sloan Research Fellow in Computer Science

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Ambuj Tewari is one of seven U-M scientists selected for Sloan Fellowships.  Dr. Tewari obtained his PhD from UC Berkeley, and joined the University of Michigan as Assistant Professor of Statistics in 2012.  He also holds a courtesy appointment at the Department of Electrical Engineering and Computer Science.  Dr. Tewari is also an Affiliate Faculty member in MIDAS.

The two-year, $60,000 fellowships are awarded to scientists “in recognition of distinguished performance and a unique potential to make substantial contributions to their field,” according to the organization’s website. Researchers are considered based on nominations, and then selected by an independent panel of senior scientists.

The Alfred P. Sloan Foundation supports early career researchers in eight fields, including chemistry, computational and evolutionary molecular biology, computer science, economics, mathematics, neuroscience, ocean sciences, and physics.

For more information, please see the U-M news release.

MDST announces Detroit blight data challenge; organizational meeting Feb. 16

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The Michigan Data Science Team and the Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS) have partnered with the City of Detroit on a data challenge that seeks to answer the question: How can blight ticket compliance be increased?

An organizational meeting is scheduled for Thursday, Feb. 16 at 5:30 p.m. in EECS 1200.

The city is making datasets available containing building permits, trades permits, citizens complaints, and more.

The competition runs through March 15. For more information, see the competition website.

Data science institutes at University of Michigan and University College London sign academic cooperation agreement

By | Al Hero, Educational, General Interest, News | No Comments
From left, Al Hero, U-M; Patrick Wolfe, UCL; and Brian Athey, U-M signed an agreement for research and educational cooperation between the University of Michigan and University College London.

From left, Al Hero, U-M; Patrick Wolfe, UCL; and Brian Athey, U-M signed an agreement for research and educational cooperation between the University of Michigan and University College London.

ANN ARBOR, MI and LONDON — The Michigan Institute of Data Science (MIDAS) at the University of Michigan and the Centre for Data Science and Big Data Institute at UCL (University College London) have signed a five-year agreement of scientific and academic cooperation.

The agreement sets the stage for collaborative research projects between faculty of both institutions; student exchange opportunities; and visiting scholar arrangements, among other potential partnerships.

“There is a lot of common ground in what we do,” said Patrick Wolfe, Executive Director of UCL’s Centre for Data Science and Big Data Institute. “Both MIDAS and UCL cover the full spectrum of data science domains, from smart cities to healthcare to transportation to financial services, and both promote cross-cutting collaboration between scientific disciplines.”

Alfred Hero, co-director of MIDAS and professor of Electrical Engineering and Computer Science at U-M, said that one of the original goals of the institute when it was founded in 2015 under U-M’s $100 million Data Science Initiative was to reach out to U.S. and international partners.

“It seemed very natural that this would be the next step,” Hero said, adding that it would complement MIDAS’s recent partnership with the Shenzhen Research Institute of Big Data in China. “UCL epitomizes the collaboration, multi-disciplinarity and multi-institutional involvement that we’re trying to establish in our international partnerships.”

Wolfe visited Ann Arbor in early January to sign a memorandum of understanding along with Hero and Brian Athey, professor of bioinformatics and the other MIDAS co-director.

The agreement lists several potential areas of cooperation, including:

  • joint research projects
  • exchange of academic publications and reports
  • sharing of teaching methods and course design
  • joint symposia, workshops and conferences
  • faculty development and exchange
  • student exchange
  • exchange of visiting research scholars.

Links:

MIDAS at U-M

UCL Big Data Institute

Follow UCL’s data science activities @uclbdi

Follow MIDAS at @ARC_UM

MIDAS Co-Director Al Hero receives 2016-2017 Stephen S. Attwood Award

By | Al Hero, General Interest, News | No Comments

Al Hero, Co-Director for the Michigan Institute for Data Science (MIDAS), has received the 2016-2017 Stephen S. Attwood Award, the highest honor awarded to a faculty member by the College of Engineering for “extraordinary achievement in teaching, research, service, and other activities that have brought distinction to the College and University.”  More information on this prestigious honor are at http://eecs.umich.edu/eecs/about/articles/2017/al-hero-receives-coe-stephen-attwood-award.html.

 

MDST Poster Wins Symposium Competition

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Today, MDST participated in the student poster competition at the “Meeting the Challenges of Safe Transportation in an Aging Society Symposium”. The poster highlights the key findings from the Fatal Accident Reporting System (FARS) competition we held earlier this year. The Michigan Institute for Data Science (MIDAS) provided MDST members access to a dataset of fatal crashes in the US, with a labeled variable indicating whether alcohol was involved in the incident, and models were judged based on how well they could predict the value of this true/false variable.

The poster describes the winning model for the competition, an ensemble of a neural network and boosted decision tree, and identifies crash time, location, and the number of passengers involved, as the most predictive variables.

We want to thank MIDAS for funding the competition, Chengyu Dai and Guangsha Shi for representing MDST at the ATLAS Symposium, and the many members of MDST who participated in the FARS Challenge.

You can download the poster from the link below.