Rezvaneh (Shadi) Rezapour is a Assistant Professor in the Department of Information Science at Drexel’s College of Computing and Informatics. Her research interests lie at the intersection of Computational Social Science and Natural Language Processing (NLP). More specifically, she is interested in bringing computational models and social science theories together, to analyze texts and better understand and explain real-world behaviors, attitudes, and cultures. Her research goal is to develop “socially-aware” NLP models that bring social and cultural contexts in analyzing (human) language to better capture attributes, such as social identities, stances, morals, and power from language, and understand real-world communication. Shadi completed her Ph.D. in Information Sciences at University of Illinois at Urbana-Champaign (UIUC) where she was advised by Dr. Jana Diesner.
Samin Aref is an educator and researcher working as an assistant professor at the University of Toronto Department of Mechanical & Industrial Engineering. Samin holds a Ph.D. in computer science from the University of Auckland (New Zealand) with a dissertation on structural analysis of signed networks. His areas of research and teaching are Network Science, Machine Learning, Operations Research, Applied Statistics, and Computational Social Science. His current research falls into three broad topics: (1) analyzing complex social and informational systems using networks, optimization, and statistical models; (2) modeling planning and decision problems in uncertain environments using mathematical programming and efficient algorithms; (3) studying the science of science across disciplines and geographies using large-scale digital trace data. More info on: 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.