Data Science

Related Faculty

Morgan G. Ames

Morgan Ames

Associate 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
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David Bamman

Associate Professor
Natural language processing, computational social science, machine learning, digital humanities
Coye Cheshire

Coye Cheshire

Professor
Trust, social exchange, social psychology, and information exchange
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John Chuang

Professor
Climate informatics; biosensory computing; incentive-centered design

Recent Publications

Federal Data Field Guide

The Federal Data Field Guide is a free resource that explains how data collection works across the federal government. It provides context and practical use cases that enable researchers and journalists to engage with the government data ecosystem fully. 

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Monitoring Nutrition Security: Perspectives from a Workshop on Nutrition Security Measurement
Modeling Language as Social and Cultural Data
Using Natural Language Processing to Describe the Use of an Online Community for Abortion During 2022: Dynamic Topic Modeling Analysis of Reddit Posts
Behavioral Innovations to Access Abortion Post-Dobbs: A Qualitative Thematic Analysis of Reddit’s r/abortion Community in 2022
Probing the limits of mobile phone metadata for poverty prediction and impact evaluation
Participant Evaluation of Blockchain-Enhanced Women’s Health Research Apps: Mixed Methods Experimental Study
Addressing contemporary threats in anonymised healthcare data using privacy engineering
Privacy guarantees for personal mobility data in humanitarian response

Data Science news

cover of the Federal Data Field Guide slide deck with title: Federal Data Field Guide and image of a platypus
New Federal Data Field Guide Helps Americans Navigate the Rich Diversity of Our Federal Data Ecosystem

Denice Ross, who served as the nation’s second U.S. Chief Data Scientist, and her former White House colleague Christopher Marcum have launched the Federal Data Field Guide.

collage of two projects
Fall 2025 MICS and MIDS Capstone Award Winners

Outstanding MICS and MIDS capstone projects.

Josh Blumenstock
Joshua Blumenstock on Using AI To End Extreme Poverty

According to a new report by a group of anti-poverty researchers that uses AI tools to achieve unusually granular data of the picture on the ground, the price tag for completely ending extreme poverty would be just $318 billion per year.

graphic displaying text and figures of people with colors coming out of their eyes
David Bamman Receives Schmidt Sciences’ Humanities and AI Virtual Institute Award

Bamman’s project bridges large-scale computational analysis in AI with humanistic scholarship in film and television.

collage of team perceive AI
Berkeley Master’s Alums Build App to Guide Visually Impaired Users Through Grocery Stores

Master of Information and Data Science (MIDS) alums Abhishek Shetty, Ana Melody Masis, Vijaykumar Krithivasan, Landon (Austin) Yurica, and Mehmet Inonu are the winners of the Sarukkai Social Impact Award, for their project, Perceive AI.

collage of three award winners
Summer 2025 MICS and MIDS Capstone Award Winners

Outstanding MICS and MIDS capstone projects.

headshot Emma lurie
Recent Ph.D. Alum Emma Lurie Mentors Award-Winning Undergraduate Team
collage of student winners
Data Science Master’s Project Fosters Sustainability by Organizing Carbon Offset Data

Master of Information and Data Science (MIDS) alums Kevin Ngoc Hoang, Xinyun (Roxy) Rong, Maggie Corry, and Roshni Suresh Tajnekar are the winners of the Sarukkai Social Impact Award, for their project, Carbon AIQ.

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Joshua Blumenstock’s Togo Research Featured in Nature Article on Using AI to Beat Poverty
logos of FALL 2024 CAPSTONE WINNERS
Fall 2024 MICS and MIDS Capstone Award Winners

Outstanding MICS, MIDS, and 5th Year MIDS capstone projects.