azjacobs at umich.edu
CV | Google Scholar
Assistant Professor of Information, School of Information
Assistant Professor of Complex Systems, College of Literature, Science, and the Arts
University of Michigan
CV | Google Scholar
ABIGAIL Z. JACOBS
Assistant Professor of Information, School of Information
Assistant Professor of Complex Systems, College of Literature, Science, and the Arts
University of Michigan
I am an Assistant Professor of Information at the University of Michigan in the School of Information and an Assistant Professor of Complex Systems in the College of Literature, Science, and the Arts. I am also an affiliate of the Center for Ethics, Society, and Computing (ESC) and the Michigan Institute for Data Science (MIDAS).
I am also a 2024 Microsoft Research AI & Society Fellow.
My current research interests are around measurement; the hidden assumptions in machine learning, focusing on measurement and validity as a lens; structure, governance, and inequality in sociotechnical systems; and social networks. Find my academic work below, on my CV, or on Google Scholar.
Since 2019, I am an Assistant Professor at the University of Michigan School of Information and the Center for the Study of Complex Systems. Previously I was a postdoctoral fellow at the Haas School of Business at UC Berkeley and a member of the Algorithmic Fairness and Opacity Working Group. I received a PhD in Computer Science from the University of Colorado Boulder. During my PhD I was fortunate to spend time at Microsoft Research NYC (intern/consulting researcher, 2015-2017) and to have funding from an NSF Graduate Research Fellowship. In 2015, I served as an organizer for the Women in Machine Learning Workshop, a technical workshop co-located with NeurIPS, and from 2018-2019 I was on the Board of Directors for Women in Machine Learning, Inc. I previously received a BA in Mathematical Methods in the Social Sciences and Mathematics from Northwestern University.
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I am also a 2024 Microsoft Research AI & Society Fellow.
My current research interests are around measurement; the hidden assumptions in machine learning, focusing on measurement and validity as a lens; structure, governance, and inequality in sociotechnical systems; and social networks. Find my academic work below, on my CV, or on Google Scholar.
Since 2019, I am an Assistant Professor at the University of Michigan School of Information and the Center for the Study of Complex Systems. Previously I was a postdoctoral fellow at the Haas School of Business at UC Berkeley and a member of the Algorithmic Fairness and Opacity Working Group. I received a PhD in Computer Science from the University of Colorado Boulder. During my PhD I was fortunate to spend time at Microsoft Research NYC (intern/consulting researcher, 2015-2017) and to have funding from an NSF Graduate Research Fellowship. In 2015, I served as an organizer for the Women in Machine Learning Workshop, a technical workshop co-located with NeurIPS, and from 2018-2019 I was on the Board of Directors for Women in Machine Learning, Inc. I previously received a BA in Mathematical Methods in the Social Sciences and Mathematics from Northwestern University.
