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

Mitigating bias in radiology machine learning: 3. Performance metrics

Aug 23, 2022

Impacts of heuristic parameters in PSO inverse kinematics solvers

May 16, 2022

Exploring Google Searches for Out-of-Clinic Medication Abortion in the United States During 2020: Infodemiology Approach Using Multiple Samples

May 15, 2022

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

May 1, 2022

Machine learning and phone data can improve targeting of humanitarian aid

Mar 16, 2022

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)

Jan 18, 2022

Micro-Estimates of Wealth and Poverty for all Low- and Middle-Income Countries

Jan 3, 2022

Self-organizing maps and Bayesian regularized neural network for analyzing gasoline and diesel price drifts

Jan 3, 2022

A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery

Dec 26, 2021

Leveraging Differential Privacy While Attending to Social and Political Commitments

Dec 15, 2021

Data Science news

Joshua Blumenstock: Machine Learning Can Help Get COVID-19 Aid To Those Who Need It Most

May 14, 2020

As the COVID-19 crisis continues, hundreds of millions of citizens of low-income countries are being left without work or income. Assistant Professor Joshua Blumenstock discusses new methods to combat this.

All’s Clear for Deepfakes? Think Again.

May 11, 2020

Despite growing sentiments that deepfakes are the “dog that never barked,” Hany Farid believes the worst is yet to come.

Photo via CITRIS and the Banatao Institute

Hany Farid, Joshua Blumenstock Awarded Seed Funding for COVID-19 Mitigation Efforts

May 15, 2020

Professors Hany Farid and Joshua Blumenstock have been awarded seed funding for their projects designed to mitigate the COVID-19 crisis by CITRIS and the Banatao Institute.

Hany Farid Joins other Bay Area Researchers to Fight Coronavirus

Apr 29, 2020

Ashkan Soltani on Apple and Google Teaming Up Against the Coronavirus

Apr 10, 2020

Aditya Parameswaran Builds App to Track the Impact of Distancing Measures

May 1, 2020

Joshua Blumenstock Addresses Housing Insecurity in the Wake of COVID-19

May 1, 2020

Professor Josh Blumenstock is leading a team that has received a grant to investigate and address eviction spikes and displacement risks related to COVID-19.