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Michigan Institute for Data Science (MIDAS) Seminars

Upcoming Seminars

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Past Seminars

NSF Priorities and Opportunities for Data Science and AI

Dr. Alfred Hero, Program Director in the NSF CISE Directorate, and the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and R. Jamison and Betty Williams Professor of Engineering, University of Michigan

1:00pm – 2:30pm in 340 West Hall

From Theory to Practice: Building Ethical and Trustworthy AI

9:00am – 5:00pm in Johnson Rooms, Lurie Engineering Center (3rd floor)

Data and AI in Society Forum Series: Generative AI, Composition, and Creativity

3:30pm – 4:30pm in Watkins Lecture Hall, Earl V. Moore Building, School of Music

Responsible Data Science and AI mini-symposium

1:30pm – 5:30pm in Rackham 4th floor Amphitheater

MIDAS Seminar | Women in Computing | Alumni

Beyond the First Portrait of a Black Hole

Katie Bouman, Assistant Professor, Computing and Mathematical Sciences, Caltech

4:00pm – 5:00pm in Remote/Virtual

U-M Data Science Annual Symposium 2020

With Prof. David Fouhey and Prof. Jason Corso

9:00am – 5:00pm in Remote/Virtual

Data Science and Politics

David Shor, SuperPAC Data Scientist, Democratic Consultant

8:00am – 5:00pm

MIDAS Reproducibility Day

2:00pm – 5:00pm

Beyond Algorithmic Fairness: What Social Justice Needs from Data Science

Kentaro Toyama, Professor of Community Information, Professor of Information, School of Information, University of Michigan

4:00pm – 5:00pm

MIDAS Reproducibility Challenge Showcase

Chris Brooks, Assistant Professor of Information – School of Information, University of Michigan

1:00pm – 2:00pm

“Is AI Racist?”

Dr. Jagadish and Other Experts, Professor, Electrical Engineering and Computer Science , Director of the Michigan Institute for Data Science

4:30pm – 5:30pm

MIDAS Reproducibility Challenge Showcase: #6

Sharon Glotzer, Professor, Chemical Engineering and Materials Science & Engineering, U-M

1:00pm – 2:00pm

MIDAS Reproducibility Challenge Showcase: Sharon Glotzer – An Open Software Approach for Reproducible Research for Materials Design

SHARON GLOTZER, Professor – Chemical Engineering and Materials Science and Engineering, University of Michigan

1:00pm – 2:00pm

MIDAS Reproducibility Challenge Showcase: #5

John Silberholz & Nigel Michki, Associate Professor, Technology & Operations, U-M & Doctoral student, Biophysics, U-M

1:00pm – 2:00pm

A Mobile/wearable Platform for Collecting Data on Sleep and Circadian Rhythms in the Time of COVID

Danny Forger, Professor of Computational Medicine, Bioinformatics, & Mathematics, U-M, University of Michigan

1:00pm – 2:00pm

A Scalable Tool for Longitudinal Twitter Analysis

Al Hero & Walter Dempsey, Professor, EECS & Engineering, U-M & Assistant Professor, School of Public Health, UM, University of Michigan

1:00pm – 2:00pm

MIDAS Seminar | Student Event

A Data Scientist Plays Games

Nick Berry, Data Scientist, Formerly with Microsoft, GameHouse, and Facebook

12:00pm – 1:30pm in Remote/Virtual

Is It Possible to Democratize AI for Business

Jen Stirrup, Regional Director

3:30pm – 4:30pm in 340 West Hall

How Language Makes Us Smart (Without Big Data)

Charles Yang, Director

3:30pm – 4:30pm in 340 West Hall

Word Embeddings: What Works, What Doesn’t, and How to Tell the Difference for Applied Research

Arthur Spirling, Deputy Director,, Center for Data Science, New York University

3:30pm – 4:30pm in 340 West Hall

Bias in Search and Recommenders Systems

Ricardo Baeza-Yates, CTO, NTENT Director, Data Science Programs,, Northeastern University, Silicon Valley Campus

3:30pm – 4:30pm in Weiser Hall

Quantifying Cell Type-Specific Changes in Transcriptional State and Gene Co-Regulation Across Multiple Datasets Using SCRANA-SEQ

Gerald Quon, Assistant Professor, University of California

2:00am – 3:00pm in Forum Hall, Palmer Commons

How Powerful Are Graph Neural Networks?

Jure Leskovec, Associate Professor, Stanford University

3:30pm – 4:30pm in Weiser Hall

Constructing Tumor-Specific Gene Regulatory Networks Based on Samples with Tumor Purity Heterogeneity

Pei Wang, PhD – Icahn School of Medicine, Mount Sinai, Professor, Department of Genetics and Geomic Sciences

3:30pm – 4:30pm in 340 West Hall

Learning & Exploiting Low-Dimensional Structure in High-Dimentional Data

David Dunson, PhD , Arts & Sciences Distinguished Professor of Statistical Science & Mathematics, Duke University

3:30pm – 4:30pm in 340 West Hall

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