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

Mitigating bias in radiology machine learning: 2. Model development
Mitigating bias in radiology machine learning: 3. Performance metrics
Impacts of heuristic parameters in PSO inverse kinematics solvers
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Exploring Google Searches for Out-of-Clinic Medication Abortion in the United States During 2020: Infodemiology Approach Using Multiple Samples

During the pandemic in the United States, there has been considerably more interest in home abortions than in minimally or nonclinically supported self-abortions. As access barriers to in-person abortion care increase due to legal restrictions and COVID-19–related disruptions, individuals may be turning to the internet for information and services on out-of-clinic medication abortions. Google searches allow us to explore timely population-level interest in this topic and assess its implications.

Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications
Machine learning and phone data can improve targeting of humanitarian aid

Here we show that data from mobile phone networks can improve the targeting of humanitarian assistance.

A Novel Cloud Architecture for Internet of Space Things (IoST)
Self-organizing maps and Bayesian regularized neural network for analyzing gasoline and diesel price drifts
Micro-Estimates of Wealth and Poverty for all Low- and Middle-Income Countries
GANArtworks In the Mood

Data Science news

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University of California Researchers Win Grant to Study Misinformation Surrounding Reproductive Health on Social Media

University of California, Berkeley, School of Information professor Coye Cheshire, along with colleagues at the UC Berkeley School of Social Welfare and UC San Francisco, recently won a $300K grant from the UC Noyce Initiative on computational precision health to study the extent of the problem, and what might be done to combat it. 

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Summer 2023 MICS and MIDS Capstone Award Winners

Outstanding MICS and MIDS capstone projects.

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Alum Nitin Kohli Wins iSchools Doctoral Dissertation Award for Outstanding Differential Privacy Research

Postdoctoral scholar and I School alum Nitin Kohli has been awarded the iSchools Doctoral Dissertation Award for his dissertation, “Leveraging Differential Privacy While Attending to Social and Political Commitments.”

two headshots; one man with child on shoulders, Kevin Lustig; man hiking, Ando Shah
Fellowship Recipients Strive to Use Technology to Understand Climate Change

Kevin Lustig and Ando Shah have been awarded the 2022–23 Quigley/Heffernan Family Environmental Fellowship.

5 women seated on chairs on a stage and one woman at a podium. Behind them is a projected slide reading "data science for science" with the Women in Data Science Berkeley logo
Look for ‘Who’s Not at the Table’ and Other Advice From Female Data Scientists

Joyce Shen, Dean Jennifer Chayes, and others shared advice at a panel at WiDS Berkeley.

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Professor John Chuang and Ph.D. Student Ando Shah Work With OpenEarth Foundation
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Fall 2022 MICS and MIDS Capstone Award Winners

Outstanding MICS and MIDS capstone projects.

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Berkeley Students Use Data Science to Model Air Pollution and Pediatric Health Outcomes

A team of MIDS students recently presented at the Stanford Maternal & Child Health Research Institute Symposium.

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Ph.D. Alum Doris Lee Selected For Forbes’ 30 Under 30

Doris Lee (Ph.D. ’21), who is 26, was featured on Forbes’s “30 Under 30” list for enterprise technology in 2023.

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How a Student Found Purpose Using Data Science in Journalism

Second-year MIMS student Ian Castro shares his experience in the new course Digital Accountability: Exploring Section 230, which provided an opportunity for data science students to communicate how technological systems work and what they mean for the public.