azjacobs at umich.edu
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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 a computational social scientist and 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).


My current research interests are around structure, governance, and inequality in sociotechnical systems; measurement; 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 NIPS, 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. 










Recent & upcoming conferences

Data & Society, The Social Life of Algorithmic Harms workshop

NeurIPS Workshop on AI for Science: Mind the Gaps. [short paper: Scientific Argument with Supervised Learning with Jeff Lockhart] December 2021

KDD Workshop on Measures and Best Practices for Responsible AI. [short paper: Measurement as governance in and for responsible AI] August 2021

Networks 2021 [paper: A large-scale comparative study of informal social networks in firms] July 2021

Networked Justice symposium at Networks 2021. [talk: Measurement as governance] June 2021

[ Please submit! Abstracts due April 15 ] Statistical Inference for Network Models symposium at Networks 2021. Organizer. June 23, 2021 

Machine learning and economic inequality conference. Invited speaker. [video: Measurement as governance, slides] April 2021

ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2021 [paper: Measurement and Fairness] March 2021

NIST Workshop on Bias in AI. Panelist. August 2020

Michigan Institute for Data Science Workshop on Learning environments in the time of COVID-19: (Towards) Evidence-Driven Innovation and Resilience at the University of Michigan. Organizer. June 2020

WebConf Workshop on Innovative Ideas in Data Science. Nominated for best paper. [short paper: Internet-Human Infrastructures: Lessons from Havana’s StreetNet] April 2020

ACM Conference on Fairness, Accountability, and Transparency (FAccT) Translation Tutorial: The Meaning and Measurement of Bias: Lessons from NLP. with Su Lin Blodgett, Solon Barocas, Hal Daumé III, & Hanna Wallach. [slides, relevant paper, video] January 2020

International Conference on Computational Social Science (IC2S2) July 2019

Women in Tech: The Future of AI Symposium. Panelist: Accountability in AI. November 2018

International Conference on Computational Social Science (IC2S2) July 2018

International Conference on Web and Social Media (ICWSM) Beyond Online Data workshop. Nominated for best paper award. June 2018

Algorithmic Fairness & Opacity Summer Workshop Panelist: Bias in Algorithms [Summary] June 2018




Research

Google Scholar

Publications

Scientific argument with supervised learning. NeurIPS Workshop on AI for Science: Mind the Gaps. [working draft]
Jeff Lockhart, A. Z. Jacobs

Measurement as governance in and for responsible AI.  KDD Workshop on Responsible AI (2021) [working draft]
A. Z. Jacobs

A large-scale comparative study of informal social networks in firms.
Management Science. (2021). [publisher link, open access pdf] 
A. Z. Jacobs, Duncan Watts. 

Measurement and fairness.
ACM Conference on Fairness, Accountability and Transparency (FAccT). (2021). [arXiv, related tutorial, slides, tutorial video] 
A. Z. Jacobs, Hanna Wallach.

Internet-human infrastructures: Lessons from Havana’s StreetNet.
WebConf Workshop on Innovative Ideas in Data Science, nominated for best paper. (2020). [preprint]
A. Z. Jacobs, Michaelanne Dye (joint work).

Translation tutorial: The meaning and measurement of bias: Lessons from natural language processing
ACM Conference on Fairness, Accountability and Transparency (FAccT). (2020). [ACM link, related tutorial, slides, tutorial video]
A. Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach.
 

Assembly in populations of social networks.
CSCW Workshop on Multi-Site Research. Short paper. (2018). [arXiv]
A. Z. Jacobs. 

Assembling thefacebook: Using heterogeneity to understand online social network assembly. ACM Web Science Conference (WebSci). (2015). [arXiv, data]
A. Z. Jacobs, Samuel F. Way, Johan Ugander & Aaron Clauset.

Learning latent block structure in weighted networks. Journal of Complex Networks 3(2), 221-248. (2015). [arXiv]
Christopher Aicher, A. Z. Jacobs & Aaron Clauset.

A unified view of generative models for networks: models, methods, opportunities, and challenges. NIPS Workshop on Networks: From Graphs to Rich Data. (2014). [arXiv]
A. Z. Jacobs & Aaron Clauset.

Efficiently inferring community structure in bipartite networks. Physical Review E 90, 012805. (2014). [arXiv, code]
Daniel B. Larremore, Aaron Clauset & A. Z. Jacobs.

Complex life cycles in a pond food web: effects of life stage structure and parasites on network properties, trophic positions and the fit of a probabilistic niche model. Oecologia 174 (3) 953-965. (2014). [publisher link
Daniel L. Preston, A. Z. Jacobs, Sarah A. Orlofske & Pieter T.J. Johnson.

Adapting the stochastic block model to edge-weighted networks. ICML Workshop on Structured Learning (SLG). (2013). [arXiv, code]
Christopher Aicher, A. Z. Jacobs & Aaron Clauset.

Detecting friendship within dynamic online interaction networks. AAAI Conference on Weblogs and Social Media (ICWSM). (2013). [arXiv]
Sears Merritt, A. Z. Jacobs, Winter Mason & Aaron Clauset.


See also:

Comparative, population-level analysis of social networks in organizations. Dissertation. 2017.

Untangling the roles of parasites in food webs with generative network models. Preprint. (2015). [arXiv]
A. Z. Jacobs, Jennifer A. Dunne, Cristopher Moore & Aaron Clauset.

Adapting to non-stationarity with growing expert ensembles. Preprint. (2011).  [arXiv]  
Cosma R. Shalizi, A. Z. Jacobs, Kristina L. Klinkner & Aaron Clauset.






Advising

Ph.D. students, UMich School of Information

& also
Efrén Cruz Cortés, MIDAS data science postdoctoral fellow
Irena Chen, UMich Ph.D. candidate in Biostatistics
Jamie Fogel, UMich Ph.D. candidate in Economics
Bernardo Modenesi, UMich Ph.D. candidate in Economics



Working with me:

Candidates interested in pursuing a PhD should apply and be admitted to the UMSI PhD program (deadline: Dec 1). If you are a University of Michigan student and are interested in doing research with me, you are welcome to email me and include your interests, major, degree, and resume/CV.

Potential postdocs: I am a faculty mentor through the MIDAS Data Science Fellows program


I was on the job market 2018-19. My job market materials are available here: Research, Teaching, Diversity statement  


Teaching

Winter 2020, 2021, 2022. SI 485 Information Analytics Projects course

Fall 2019, 2020, 2021. CMPLXSYS 501 Foundations of Complex Systems. [syllabus]


Contact
Online:

Find me on Google Scholar, or in person as azjacobs + umich.edu. I almost never tweet as @az_jacobs.



Offline:

I often go by Abbie and as a consequence will respond to Abby, Abbi, Aby, and other creative variations of Abigail.


Abigail Z. Jacobs she/her/hers
azjacobs + umich + edu