November 10

9:00 – Opening Remarks

H.V. Jagadish
Director, MIDAS | Professor of Electrical Engineering and Computer Science

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9:05 – Keynote: Data Feminism

Co-Sponsored by:

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10:05 – Break

10:10 – Research Talks Session 1

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11:50 – Networking Session with Speakers

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12:15 – Break

12:45 – Poster Session

The 2020 Symposium’s poster sessions will be hosted on via the College of Engineering’s CareerFair+ tool.

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14:45 – Mini-Workshops

Agent-based modeling and systemic racism

Lead Presenter: Holly Hartman, PhD candidate, Biostatistics, University of Michigan

In this workshop, participants will gain a better understanding of systemic bias and how algorithms may continue to promote inequity. Participants will learn about agent based methods, a tool which can be used to examine algorithmic fairness. There will be opportunities to brainstorm ideas for new research projects within the participants’ fields.

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Data Science and Natural Language Processing to find rare classes of entities from text

Lead Presenter: VG Vinod Vydiswaran, Assistant Professor, Learning Health Sciences and School of Information, University of Michigan

Natural language processing (NLP) and Data Science methods, including recently popular deep learning-based approaches, can unlock information from narrative text and have received great attention in the medical domain. Many NLP methods have been developed and showed promising results in various information extraction tasks, especially for rare classes of named entities. These methods have also been successfully applied to facilitate clinical research. In this workshop, we will highlight some methods and technologies to identify rare concepts and entities in text in the medical domain as well as other “open” domains.

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Introduction to Python for community members and K-12 teachers and students

Lead Presenter: Fred Feng, Assistant Professor Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn

This hands-on workshop is tailored to audiences who do not have prior programming experience. The first half of the workshop covers Python programming basics and the second half covers performing data analysis and visualization in Python with real-world data. The audiences are encouraged to follow along with the examples on their own computer. We will use an online browser-based environment (Google Colab), and no software installations on your computer are required. Attendees will need a Google account and will sign in to their browser in order to use this cloud-based tool during the workshop.

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Scrubbing and cleaning of sensitive data

Lead Presenter: Jonathan Reader, Programmer/Data Analyst, Neurology, University of Michigan

  • Nicolas May, Data Systems Manager,  Neurology, University of Michigan
  • Kelly Bakulski, Research Assistant Professor, School of Public Health, University of Michigan

Before analysis, data must be retrieved, scrubbed of identifiable information, cleaned (e.g., addressed missing data, reshaped appropriately), and delivered. Using biomedical and transportation datasets as examples of how this generalizable process works, this workshop will walk attendees through a real-world pipeline used to process and deliver datasets. Documentation and code will be made available through GitLab to allow for coding along with the demonstration. As a result of this workshop, attendees will leave with a practical template for implementing their own a data science pipeline.

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Stitching Together the Fabric of 21st Century Social Science

Mike Mueller-Smith, Assistant Professor, Department of Economics, University of Michigan: “The Criminal Justice Administrative Records System: Assessing the Footprint of the U.S. Criminal Justice System”
David Johnson, Director and Research Professor, Panel Study of Income Dynamics and Survey Research Center, University of Michigan: “Building America’s Family Tree: The Panel Study of Income Dynamics”
Trent Alexander, Associate Director and Research Professor, ICPSR, University of Michigan: “Creating a New Census-based Longitudinal Infrastructure”
Joelle Abramowitz, Assistant Research Scientist, Survey Research Center, University of Michigan: “The Census-Enhanced Health and Retirement Study: Optimal Probabilistic Record Linkage for Linking Employers in Survey and Administrative Data”


Today’s pressing questions of social science and public policy demand an unprecedented degree of data scope and integration as we recognize the cross-cutting dynamics of economics, political science, sociology, demography, and psychology. This panel features four UM researchers who are pushing the frontier of data construction and linkage in coordination with partners at the U.S. Census Bureau.

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The state of the art in Automated and Semi-Automated Video Coding

Lead Presenter: Jason Corso, Professor, Electrical Engineering and Computer Science, University of Michigan

  • Maggie Levenstein, Director and Research Professor, ICPSR and School of Information, University of Michigan
  • Susan Jekielek, Assistant Research Scientist, ICPSR, University of Michigan
  • Donald Likosky, Professor, Department of Cardiac Surgery, University of Michigan

Video is being acquired at an alarming rate across domains, including social research, healthcare, entertainment, sporting and more.  The ability to code this video—attribute certain properties, labels, and other annotations—in support of analytical domain-relevant questions is critical; otherwise, human coding is required.  Human coding, however, is laborious, expensive, not repeatable, and, worse, often error prone.  Video coding, an area within artificial intelligence and computer vision, seeks automated and semi-automated methods to support more effective and robust video coding.  This workshop will review the state of the art in video coding from a capabilities, limitations and tooling perspective and present real-world use-cases.

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16:15 – Open Networking

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17:15 – End of Day

November 11

9:00 – Research Talks Session 2

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10:40 – Poster Awards

Trisha Fountain
Education Program Manager, MIDAS

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Poster Award Winners

  • Best Overall Poster, Most Effective Use of Data: April Kriebel – Department of Computational Medicine and Bioinformatics, Medical School “Integrating single-cell datasets with partially overlapping features using nonnegative matrix factorization”
  • Outstanding Project Design: Bruno Castelo Blanco – Marketing Department, Ross “Gaming Addiction: An Empirical Analysis”
  • Most Likely to Make an Impact in the Field: Alex Ritchie – EECS, College of Engineering “Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations”
  • Outstanding Undergraduate Poster: Nabeel Rehemtulla – Department of Astronomy, LSA “Non-Parametric Spherical Jeans Mass Estimation with B-Splines”

11:00 – Fireside Chat: Advancing Science and Social Change through Data Science and AI Research and Careers

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12:00 – Closing Remarks, Networking Rooms open for additional discussion

H.V. Jagadish
Director, MIDAS | Professor of Electrical Engineering and Computer Science

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Join Networking Session – Starts at 12:15pm

Program Committee

Libby Hemphill
School of Information

Justin Johnson
Computer Science and Engineering

Danai Koutra
Computer Science and Engineering

Jing Liu

Christopher Miller

Christopher Miller

Sam Mukherji
Music Theory

Arvind Rao
Computational Medicine and Bioinformatics, and Radiation Oncology

Zhenke Wu

Zhenke Wu

Symposium Sponsors

Ann Arbor Spark



External Partners Supporting the Symposium

Quicken Loans

American Mathematical Society

General Dynamics


United States EPA