Przemek Grabowicz
Interests
Fair and explainable machine learning, computational social science, social computing systems, network science, causality.
Research
Professor Grabowicz's research contributes statistical methods to understand and augment fundamental social processes in systems of our information society. The ambition of his research is to design fair and representative social computing systems, such as rating systems in social media, predictive models of human decision-making, and recommender systems. Important questions concerning the design of these systems include: how to train non-discriminatory machine learning models and how to prevent biases in social evaluations? Professor Grabowicz studies fairness, social influence, group formation, information diffusion, and information processing using multilevel probabilistic graphical models, information theory, network science, and causal inference.
Biography
Ph.D., Interdisciplinary Physics, University of Balearic Islands (2013), M.Sc., Applied Physics, Warsaw University of Technology (2008). Professor Grabowicz joined the College of Information and Computer Sciences of the University of Massachusetts Amherst in Fall 2018 as a Research Assistant Professor. Prior to this, from 2013 to 2018, he was a postdoctoral researcher at the Max Planck Institute for Software Systems in Saarbruecken, Germany.
Activities & Awards
Professor Grabowicz received a prestigious computational social science grant from the Volkswagen Foundation in 2017, the Data Challenge prize from the Waterloo Institute for Complexity & Innovation in 2013, the Jae Predoc fellowship from the Spanish National Research Council in 2009, and the M. Krol scholarship in 2004-2008 from the Warsaw University of Technology. He has served as an Area Chair for ECML-PKDD and ICWSM, on the program committees for several scientific conferences, including WWW, ICWSM, WebSci, SocInfo, IC2S2, NetSci, and as a reviewer for multiple scientific journals. He signed the Cost of Knowledge open letter in 2012.