Data Science

Related Faculty

Morgan G. Ames
Assistant Adjunct Professor
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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Associate Professor
Natural language processing, computational social science, machine learning, digital humanities
Josh Blumenstock
Associate Professor
Alumni (PhD 2012)
Development Economics, Data Science, Machine Learning, Econometrics, ICTD
Coye Cheshire
Professor
Trust, social exchange, social psychology, and information exchange
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Professor
Bio-sensory computing; brainwave authentication; information economics and policy
Photo of Aditya Parameswaran
Assistant Professor (I School and Computer Science)
Data management, interactive or human-in-the-loop data analytics, information visualization, crowdsourcing, data science
Steven Weber
Professor (I School and Dept. of Political Science); Faculty Director, Center for Long-Term Cybersecurity
International politics, international business, and the information economy; Cybersecurity; Behavioral economics within Information Systems

Recent Publications

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

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.

Diagram of a timeline of events for generating a recommendation for a sample learner
Mar 21, 2017

The path towards a more democratized learner success model for MOOCs has been hampered by a lack of capabilities to provide a personalized experienced to the varied demographics MOOCs aim to serve.  Primary obstacles to this end have been insufficient support of real-time learner data across platforms and a lack of maturity of recommendation models that accommodate the learning context and breadth and complexity of subject matter material in MOOCs. In this paper, we address both shortfalls with a framework for augmenting a MOOC platform with real-time logging and dynamic content presentation capabilities as well as a novel course-general recommendation model geared towards increasing learner navigational efficiency. We piloted this intervention in a portion of a live course as a proof-of-concept of the framework. The necessary augmentation of platform functionality was all made without changes to the open-edX codebase, our target platform, and instead only requires access to modify course content via an instructor role account.

The organization of the paper begins with related work, followed by technical details on augmentation of the platform’s functionality, a description of the recommendation model and its back-tested prediction results, and finally an articulation of the design decisions that went into deploying the recommendation framework in a live course.

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Data Science news

studnets sitting on steps at UC Berkeley

New UC Berkeley public interest tech initiative ‘Fiat Justice Scholars’ will teach a diverse group of undergraduates both technical skills, and, how to think critically about the application of those skills.

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Tony Di Sera (MIDS ’21) has been awarded the Jack Larson Data for Good Fellowship for her wide-ranging contributions to genomic research using data science and visualization.

ScholarPhi

ScholarPhi is an augmented reading interface that makes scientific papers more understandable and contextually rich

An image of Arnobio Morelix and his book 'Rebooted'

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

Video from the BBC

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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