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Martin Saveski is an Assistant Professor at the University of Washington's Information School. His research focuses on developing tools for analyzing large-scale social data to understand social structures and behaviors online, particularly regarding their impact on the design of digital social systems. Recent work has concentrated on reducing political polarization online and improving the quality of online conversations, utilizing causal inference methods in social systems. His research intersects the fields of Social Networks, Machine Learning, and Causal Inference. Martin's work is published in venues such as ICWSM, WWW, and KDD, and he has collaborated with researchers from platforms like Twitter, Facebook, and LinkedIn. His research has earned him recognition, including an honorable mention at the WWW '18 conference and features in prominent media outlets such as The New York Times, NPR, and MIT Technology Review.
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