Data Science

Related Faculty

Morgan Ames

Assistant Professor of Practice
Alumni (MIMS 2006)

Science and technology studies; computer-supported cooperative work and social computing; education; anthropology; youth technocultures; ideology and inequity; critical data science

Daniel Aranki

Assistant Professor of Practice

Predictive medicine; artificial intelligence; machine learning; tele-health; information disclosure; privacy; security.

David Bamman

Associate Professor

Natural language processing, computational social science, machine learning, digital humanities

Coye Cheshire

Professor

Trust, social exchange, social psychology, and information exchange

John Chuang

Professor

Biosensory computing; climate informatics; information economics and policy

Aditya Parameswaran

Associate Professor (I School and EECS)

Data management, interactive or human-in-the-loop data analytics, information visualization, crowdsourcing, data science

Recent Publications

teaser image of book cover - O'Reilly Media - 97 Things About Ethics Everyone in Data Science Should Know

Securing Your Data From Breaches Will Help Us Improve Healthcare

Aug 2, 2020

When you go to a new healthcare clinic in the United States, doctors and nurses pull up your patient record based on your name and birthdate. Sometimes it’s not your chart they pull up. This is not only a healthcare problem; it’s a data science problem.

Migration and Social Networks: New Insights from Novel Data

May 9, 2020

This Thing Called Fairness: Disciplinary Confusion Realizing a Value in Technology

Nov 14, 2019

Information-intensive innovation: the changing role of the private firm in the research ecosystem through the study of biosensed data

Aug 16, 2019

Sensing is Believing: What People Think Biosensors Can Reveal About Thoughts and Feelings

Jun 13, 2019

The strength of long-range ties in population-scale social networks

Dec 31, 2018

Don't forget people in the use of big data for development

Dec 30, 2018

Machine Learning for the Developing World using Mobile Communication Metadata

Dec 10, 2018

The Transformation of Gender in English-Language Fiction

Feb 13, 2018

This essay explores the changing significance of gender in fiction, asking especially whether its prominence in characterization has varied from the end of the eighteenth century to the beginning of the twenty-first. The authors found that while gender roles were becoming more flexible, the space actually allotted to (real, and fictional) women on the shelves of libraries was contracting sharply.

Imputing KCs with Representations of Problem Content and Context

May 8, 2017

Data Science news

Parameswaran accepts the 2019 VLDB Early Career Research Contributions Award.

Democratizing Data Science: Parameswaran Receives the 2019 VLDB Award

Sep 27, 2019

Assistant professor at the Berkeley School of Information, Aditya Parameswaran, has been awarded the 2019 Very Large Data Bases Early Career Award.

Santamaria Ots locating cities in need of relief supplies.

“Data for Good” Fellowship Awardee Aims to Empower Puerto Rican Citizens

Sep 18, 2019

In the summer of 2019, Daniel Santamaria Ots received the Jack Larson Data for Good Fellowship for his research in Puerto Rico.

Marti Hearst is a 2019 Bloomberg Data Science Research Grant Winner

Jun 11, 2019

Professor Marti Hearst is one of six recipients of a Bloomberg Data Science Research Grant for research on Unsupervised Abstractive News Summarization.

Josh Blumenstock Uses Phone Data to Reveal Socioeconomic Status

Feb 23, 2019

Josh Blumenstock at the Artifical Intelligence for Economic Development conference

Josh Blumenstock Honored for Research in the Public Interest

Apr 16, 2019

Prof Blumenstock received the Faculty Award for Research in the Public Interest for his research at the intersection of machine learning and development economics.

Joshua Blumenstock: The Knowns and Unknowns of Big Data and Poverty Alleviation

Mar 18, 2019

Joshua Blumenstock cautions that new digital methods of approaching issues of poverty must be used as a complement to more traditional approaches.

Anna Jacobson's data visualization "The Building Blocks of Gender Equality"

MIDS Student’s Feminist Visualization wins Data Science Challenge

Jan 29, 2019

“What would it mean to do feminist data science?” This question, raised by a fellow MIDS classmate, sparked the idea for Anna Jacobson’s award-winning data visualization “The Building Blocks of Gender Equality.”

Image from The Big Sleep via The Guardian

The Guardian Notes David Bamman’s Findings on Representation of Women in Literature

Feb 19, 2018

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.

Big Data Meets Literary Analysis: Digital Humanities Research at the I School

Mar 21, 2018

Machine learning and big data don’t intuitively go hand-in-hand with studies of literary fiction; however, new research from Professor David Bamman, using a machine learning algorithm and natural language processing, revealed surprising trends related to gender in novels of the 20th century.

The Economist Explores David Bamman’s Algorithmic Literary Analysis

Mar 8, 2018