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The Human-Centered Data Science research group (HCDS) focuses on the human factors in the conception, use, and understanding of data. Positioned in the intersection of data science, social science, HCI, and CSCW we are interested in understanding and exploring human practices enabled by technology. We combine both quantitative and qualitative methods, and work with computational methods such as statistics, machine learning, network analysis together with qualitative methods such as ethnography, interviews, and observations. Our research aims to contribute to often overlooked human-centered dimensions of data science such as individual differences, domain-expertise, design implications, and societal impact. Within HCDS we work across several topics, including digital media platforms, information visualization, crowd sourcing, affective computing, behavioral modeling, and societal challenges related to digital infrastructure more broadly.