azjacobs at umich.edu
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 a computational social scientist and an Assistant Professor at the University of Michigan in the School of Information and the Center for the Study of Complex Systems.


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.


I am currently recruiting students for the upcoming year. 
Interested candidates should apply and be admitted to the UMSI PhD program (deadline: Dec 1, 2019). 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.


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. 


This past year I was on the job market.
Job market materials: Research, Teaching, Diversity statement  







Recent & upcoming conferences

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

International Conference on Computational Social Science (IC2S2, July 2019)

Women in Tech: The Future of AI Symposium. Panelist: Accountability in AI. (November 18, 2018) 

International Conference on Computational Social Science (IC2S2, July 2018)

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

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

International Conference on Network Science (NetSci, June 2018)

NetSci Symposium on Integration of Empirical Data in Network Epidemiology (June 2018)




Research

Google Scholar

In prep

When do networks matter? A comparative study of informal social networks in firms. [submitted]
A. Z. Jacobs, Duncan Watts.

Measurement and fairness. [submitted]
A. Z. Jacobs, Hanna Wallach.


Publications


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.

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.

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.

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



See also:

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

Why so few? Network science with populations of networks. [in prep via dissertation]
A. Z. Jacobs.

Activity bias in network measurement. [in prep via dissertation]
A. Z. Jacobs, Duncan Watts.





Teaching


Fall 2019. LSA CMPLXSYS 501 Foundations of Complex Systems. [syllabus] 

Winter 2020. SI 485 Information Analytics Projects course.


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
azjacobs + umich + edu