Rezvaneh (Shadi) Rezapour is a Ph.D. candidate at the School of Information Sciences (the iSchool) at the University of Illinois at Urbana-Champaign (UIUC) where she has served as a teaching assistant for social network analysis courses. Shadi’s research is focused on computational social science. In particular, she develops models to extract meaningful information from (online) social discourse. More broadly, she is interested in combining methods from natural language processing, machine learning, and network analysis with social science theories to better understand real world behaviors, attitudes and cultures. For more information see https://sites.google.com/view/rezapour/home.
Samin Aref holds a Ph.D. in computer science from University of Auckland (New Zealand) with a dissertation on structural analysis of signed networks. He works as a research scientist at the Laboratory of Digital and Computational Demography, Max Planck Institute for Demographic Research (Germany) where he has taught hand-on networks courses. His research interests include computational social science, analyzing big data, network science, bibliometrics, and machine learning. For more information, see https://saref.github.io/.
Ly Dinh is a Ph.D. candidate at the iSchool of UIUC, where she teaches a graduate-level course on social network analysis. Her research topics focus on how research methods, such as network analysis, social simulation models, and text analysis, can be used to advance our understanding of various social and organizational systems. Her current projects place network science at the core to understand and explain a number of social and organizational phenomena ranging from egocentric networks to interagency emergency response networks. For more information, see https://publish.illinois.edu/lydinh-uiuc/.
Jana Diesner is an Associate Professor at the iSchool of UIUC, where she leads the Social Computing Lab. Her research in social computing and human-centered data science combines methods from natural language processing, social network analysis and machine learning with theories from the social sciences to advance knowledge and discovery about interaction-based and information-based systems. Jana got her Ph.D. (2012) in Societal Computing from the School of Computer Science at Carnegie Mellon University. For more information, see http://jdiesnerlab.ischool.illinois.edu.