Category

Al Hero

NASEM Webinar: Data Science for Undergraduates – Opportunities & Options

By | Al Hero, Educational, News

As our economy, society, and daily life become increasingly dependent on data, new college graduates entering the workforce need to have the skills to analyze data effectively.

At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine organized a study to explore what data science skills are essential for undergraduates and how academic institutions should structure their data science education programs.

We invite you to join us for a report release webinar on May 2, 2018 at 11am ET.

During this webinar, study co-chairs Laura Haas and Alfred Hero will discuss the report’s findings and recommendations, followed by a question and answer session with webinar participants.

Register

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

By | Al Hero, Educational, General Interest, Research

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.

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

By | Al Hero, Educational, General Interest, News
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

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.

 

MIDAS co-sponsoring Transportation Research Board’s Transformational Technologies symposium — Oct. 31 & Nov. 1 in Detroit

By | Al Hero, Educational, Events, General Interest, News

This symposium will bring together leaders from the public and private sectors and academia to meet the challenges posed by deployment of transformational transportation technologies. MIDAS affiliated faculty members Carol Flannagan, Al Hero and Pascal Van Hentenryck will be speaking.

For more information, visit the event website.

Slate Article: Reproducibility crisis is good for science

By | Al Hero, General Interest, News

Recently it has been shown that many published results in biology, epidemiology,  psychology have failed to reproduce when reanalyzed with new data. This article in Slate argues that the reproducibility crisis is actually good for science, creating an awareness of the need for careful experimental design and and statistical data analysis. MIDAS is committed to promoting reproducible research practices.