Los Angeles
Summer Institute in Computational Social Science Partner Site

June 17 - June 28, 2019 | University of California at Los Angeles (UCLA)

Partner location for SICSS organized at Princeton University

From Monday, June 17 to Friday, June 28, 2019, the California Center for Population Research (CCPR) will sponsor a partner site for the Summer Institute in Computational Social Science (SICSS) in Los Angeles. The purpose of the Summer Institute is to bring together graduate students, postdoctoral researchers, and early career faculty interested in computational social science. The Summer Institute is open to both social scientists (broadly conceived) and data scientists (broadly conceived).

The site is organized by former participants of the 2018 SICSS workshop and will feature live streams of the primary location at Princeton in addition to local speakers who will present on cutting-edge computational social science research. Topics covered in coordination with the Princeton site will include text analysis, digital data collection, online field experiments, non-probability sampling, agent based modeling, and ethics. A site-specific focus at this partner institute will be machine-learning methods for causal inference. During the first week, participants will gain hands-on experience through group work implementing the material from the lectures. For the second week, participants will develop research projects drawing on the content from the first week and form teams to implement these projects.

SICSS-Los Angeles will be held at the University of California at Los Angeles (UCLA). There is no cost to participate, and we will provide refreshments for all on-site days (see schedule for details). Applications are open to all interested individuals regardless of location, but we cannot provide support for travel and lodging in Los Angeles.

We invite applications from graduate students, postdoctoral researchers, and untenured faculty within 7 years of their Ph.D. SICSS-Los Angeles is committed to diversity and inclusion in computational social science, and we particularly encourage applicants from groups currently underrepresented in the field. We anticipate to admit roughly twenty participants.

Participants with less experience with social science research will be expected to complete additional readings in advance of the Institute, and participants with less experience coding will be expected to complete a set of online learning modules on the R programming language. To support this preparatory work, participants will have access to a teaching assistant who will hold online office hours before the Institute.

Application materials will be due on Sunday, April 14, 2019. Note that this is six weeks after the main application deadline and after decisions about the main location are expected to have been made. If you have also applied to the Princeton location and have not yet heard from them at the time of your submission, please let us know in your application.


We are grateful to the California Center for Population Research for their sponsorship of the partner site.

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Friedolin Merhout

Friedolin Merhout is a doctoral student in the Duke Sociology department. He enjoys exploring how computational methods provide a new lens to view longstanding social science debates, and pondering the potential inherent in the wealth of digital trace data. Before starting the doctoral program at Duke, he earned a BA from Freie Universitaet in his hometown Berlin.

Alina Arseniev-Koehler

Alina Arseniev-Koehler is currently a graduate student at the University of California Los Angeles pursuing a PhD in Sociology. Substantively, her research interests include culture, cognitive sociology, language, and health and illness. Methodologically, she is interested in computational social science and machine-learning, with a focus on the computational analysis of language. Her Master’s research aimed to provide a cognitively plausible, computational account of the schemata activated by news reporting on obesity. Alina also enjoys learning and teaching new computational techniques and helps coordinate the Computational Sociology Working Group at UCLA.

Jennie E. Brand

Jennie E. Brand is Professor of Sociology and Statistics at the University of California, Los Angeles (UCLA). She is Director of the California Center for Population Research (CCPR) and Co-Director of the Center for Social Statistics (CSS) at UCLA. She is Chair-Elect of the Methodology Section of the American Sociological Association (ASA) and an elected Board Member of the International Sociological Association (ISA) Research Committte on Social Stratification and Mobility (RC28). Prof. Brand is a member of the Board of Overseers of the General Social Survey (GSS) and a member of the Technical Review Committee for the National Longitudinal Surveys Program at the Bureau of Labor Statistics. She received the ASA Methodology Leo Goodman Mid-Career Award in 2016, and honorable mention for the ASA Inequality, Poverty, and Mobility William Julius Wilson Mid-Career Award in 2014. Prof. Brand studies social stratification and inequality, mobility, social demography, education, and methods for causal inference.

Local Speakers

To be announced.

Schedule and materials

Monday June 17, 2019 - To be announced.

- The schedule will be posted in the coming weeks.