Data Science

Related Faculty

Alumni (MIMS 2006)
Assistant Professor of Practice
Science and technology studies; computer-supported cooperative work and social computing; education; anthropology; youth technocultures; ideology and inequity; critical data science
Assistant Professor of Practice
Predictive medicine; artificial intelligence; machine learning; tele-health; information disclosure; privacy; security.
Associate Professor
Natural language processing, computational social science, machine learning, digital humanities
Professor
Trust, social exchange, social psychology, and information exchange
Professor
Biosensory computing; climate informatics; information economics and policy

Data Science news

Analysis from I School Professor David Bamman finds proportion of female authors and characters fell after 19th century, with male authors remaining ‘remarkably resistant’ to writing women.

Professor David Bamman’s machine-learning algorithm analyzed the presentation of gender in more than 100,000 novels.

Position will begin July 2016; applications are due December 14.
Bamman’s work applies natural language processing and machine learning techniques to empirical questions in the humanities and social sciences.
The dataset could help answer whether it’s possible to accurately use consumer-grade devices to interpret attention level in a problem-solving test. The class hopes that other researchers will be able to repeat the experiment with even larger subject pools.
Capped by a keynote from Obama adviser John Podesta, a day-long workshop brought together the worlds of government, business, the law, and academia for what assistant professor Deirdre Mulligan called “a frank and honest conversation about our values,” and about how to balance those values with the omnipresent, often invisible collection of data about every aspect of our lives.
The School of Information has officially started its new online Master of Information and Data Science (MIDS) program, preparing students to solve real-world problems using complex and unstructured data.
Pardos is an expert in the emerging field of educational data mining — applying data science methodologies to online learning environments to understand student learning.
A new student research project analyzes the text of Yelp restaurant reviews to automatically reveal the underlying topics discussed by the reviewers — and predict the rating the restaurant would have received based on each individual topic.