Nick Adams, PhD, was a full-time research fellow at the Berkeley Institute for Data Science (BIDS). He is a sociologist, and his substantive work analyzes protester and police interactions as revealed through 8,000 news accounts of nearly 200 US Occupy campaigns. His TextThresher software provides the human-powered machinery to process these data in high quantity with high quality. A builder of research communities across UC Berkeley's campus, Nick founded and leads the Computational Text Analysis Working Group at Berkeley’s D-Lab and BIDS' Text Across Domains (Text XD) initiative. He also serves on the Social Science Research Council’s Committee on Digital Culture and is a contributing editor to Mobilizing Ideas, the online journal of social movements research.
Elena Glassman was an EECS postdoctoral researcher at the Berkeley Institute of Design, advised by Bjoern Hartmann. She earned her EECS PhD at MIT CSAIL in August 2016, where she created scalable systems that analyze, visualize, and provide insight into the code of thousands of programming students. Prior to entering the field of human-computer interaction, she earned her M.Eng. in the MIT CSAIL Robot Locomotion Group. She was a visiting researcher at the Stanford Biomimetics and Dextrous Manipulation Lab and a summer research intern at both Google and Microsoft Research, working on systems that help people teach and learn. Before receiving the BIDS Moore/Sloan Data Science Fellowship, she was awarded the Intel Foundation Young Scientist Award, both the NSF and NDSEG graduate fellowships, the MIT EECS Oral Master’s Thesis Presentation Award, a Best of CHI Honorable Mention, and the MIT Amar Bose Teaching Fellowship for innovation in teaching methods.
Alexandra is a BIDS data science fellow and a postdoctoral scholar working with Tom Griffiths in the Institute of Cognitive and Brain Sciences. She got her PhD in cognitive and information sciences from the University of California, Merced, in December 2015.
Her work explores human communication in data-rich environments. From capitalizing on large-scale real-world corpora to capturing multimodal experimental data, her research seeks to understand how context changes communication dynamics. Broadly, her work integrates computational and social perspectives to understand interpersonal interaction as a nonlinear dynamical system.
Relatedly, Alexandra also develops research methods to facilitate quantitative research on interaction and encourages others to use data-rich computational methods through teaching and service. As part of that effort, she works with the Center for Data on the Mind to foster the application of big data to questions about cognition and behavior.