Eaman Jahani

Social Scientist and Statistician at University of Maryland

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Assistant Professor at University of Maryland Business School

Email: eaman [at] umd [dot] edu

I am an assistant professor of Information Systems at University of Maryland Business school. Previously, I was a postdoctoral associate at UC Berkeley department of Statistics until January 2024. I received a dual PhD in Social and Engineering Systems and Statistics from IDSS and the Statistics and Data Science Center at MIT.

My PhD research is focused on micro-level structural factors, such as network structure, that contribute to unequal distribution of resources or information. As a computational social scientist, I use methods from network science, statistics, experiment design and causal inference. I am also interested in understanding the collective behavior in institutional settings, the institutional mechanisms that promote cooperative behavior in networks, or in contrast lead to unequal outcomes for different groups.

In a previous life, I worked at Google New York City as a software engineer from 2011 to 2015. At Google, I worked on several products around the AdWords ad auction. We analyzed the ad auction dynamics and developed relevant suggestions for advertisers. I received my Bachelor’s and Master’s degrees in Computer Science both from the University of Michigan - Ann Arbor.

news

Aug 25, 2023 I will be joining the Smith School of Business at the university of Maryland as an assistant professor, starting January 2024.
Aug 10, 2023 New paper in collaboration with Yuan Yuan on the impact of vaccination heterogeneity is out.
Jul 15, 2023 So glad that one my PhD dissertation chapters is finally out in PNAS. Also check out the accompanying public data release.
Nov 1, 2022 New paper on how common enemies cannot reduce inter-group polarization in the US is out. Collaboration with amazing researchers at SICSS pays off.
Oct 1, 2022 New pre-print on the distribution of long ties in networks and brokerage out. So glad for this work to finally be out.