Data Science

Related Faculty

Morgan G. Ames

Morgan Ames

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
Daniel Aranki

Daniel Aranki

Assistant Professor of Practice
Predictive medicine; artificial intelligence; machine learning; tele-health; information disclosure; privacy; security.
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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
Biosensory computing; climate informatics; information economics and policy

Recent Publications

Philosophy of Computational Social Science
Improving efficacy attribution in a self-directed learning environment using prior knowledge individualization
Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization. Technology, Knowledge and Learning
How the Machine ‘Thinks:’ understanding opacity in machine learning algorithms
Predicting Poverty and Wealth from Mobile Phone Metadata
Data mining and education
Essays on the Economic Impacts of Mobile Phones in Sub-Saharan Africa
Linked Data and Service Orientation
Modeling individualization in a bayesian networks implementation of knowledge tracing
Improving Federal Spending Transparency: Lessons Drawn from Recovery.gov

Data Science news

An image of Arnobio Morelix and his book 'Rebooted'
New Book by Data Science Alumnus Looks at the Post-Pandemic Economy

Rebooted: An Uncommon Guide to Radical Success and Fairness in the New World of Life, Death, and Tech, by Arnobio Morelix, examines the opportunities and challenges that are on the horizon for businesses in the post-pandemic economy.

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Alumni Win Grant To Develop EdTech Capstone Project

TeacherPrints, a project developed in MIDS Capstone recently won a $25,000 grant as a Catalyst Prize winner by the Futures Forum on Learning.

Emily Aiken, doctoral student at the UC Berkeley School of Information
The Economist Highlights Ph.D. Student Emily Aiken’s Research Using Machine-Learning and Mobile-Phone Data
Video from the BBC
How Data Science and Satellite Images Are Helping One Country Hand Out Cash

In a short film, Professor Josh Blumenstock explains how Berkeley researchers have facilitated a high-tech way for the government of Togo to identify people who need financial help in the pandemic and send them emergency cash.

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Listen: Josh Blumenstock on Using Satellite Photos and Mobile Phones to Help Distribute Cash Aid
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Josh Blumenstock is Using Big Data to Combat Extreme Poverty in Togo
Josh Blumenstock
Blumenstock’s AI Work Brings Cash Aid to Rural Residents in Togo
Josh Blumenstock
Blumenstock Works With Togo Government to Identify and Deliver Aid to People in Need

Joshua Blumenstock has worked closely with top government officials in Togo to develop an advanced data-driven system for identifying people in need and delivering financial aid. 

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Summer and Fall 2020 MIDS and MICS Award Winners

Outstanding MICS and MIDS capstone projects, and distinguished teaching awards.

Jennifer Chayes
Dean Jennifer Chayes Dedicated to Advancing Diversity in Computing