Speaker(s)
Nick Adams
Former BIDS Research Fellow Nick Adams, PhD, is now Founder & Chief Scientist of Goodly Labs, an organization that provides collaborative online resources and opportunities that enable citizen scientists to engage with publicly available data. He is a sociologist, data scientist, and creator building tools and experiences that help people find common ground and build a better society. In a career motivated by his aspiration to improve the world, Adams has led electoral campaigns, directed the national security division of a think tank, completed ground-breaking research on police/protester interactions, constructed and shared massive and intricate datasets, invented new natural language processing methodologies and collaborative software, and instructed hundreds of students on topics including classical and contemporary social theory, social science methods, social psychology, political sociology, deviance and social control, and text analysis. Adams has founded and led multiple successful and surviving organizations, including Thusly Inc., UC Berkeley's Text Across Domains, the Computational Text Analysis Working Group, and his non-profit Goodly Labs, the sociotechnical skunkworks behind Public Editor, Demo Watch, Research Ready, and Same Page. His work has appeared in academic journals as well as The New York Times, Roll Call, The Atlantic, and Reader's Digest. He has been funded by the Alfred P. Sloan Foundation, the MCcune Foundation, Schmidt Futures, the Berkeley Institute for Data Science, the Pritzker Family Fund, SAGE Publishing, the Social Science Research Council, and the National Science Foundation.
Elena Glassman
Former BIDS Data Science Fellow Elena Glassman is an Assistant Professor of Computer Science at the Harvard Paulson School of Engineering & Applied Sciences (SEAS), and the Stanley A. Marks & William H. Marks Professor at the Radcliffe Institute for Advanced Study. At Berkeley, 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 Paxton
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.