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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Assistant 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
Associate Dean and Head of School; Faculty Director, Center for Long-Term Cybersecurity; Professor (I School and Dept. of Political Science)
International politics, international business, and the information economy; Cybersecurity; Behavioral economics within Information Systems

Recent Publications

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

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Ph.D. student Lucy Li Awarded Best Paper by the American Educational Research Association

Doris Lee

Lee aims to design systems that provide automated recommendations in visual data exploration and machine learning

David Bamman

David Bamman’s BookNLP project will receive funding from the National Endowment for Humanities (NEH) to expand its scope to include German, Japanese, Russian and Spanish languages.

Daniel Alvarez

MIDS student Daniel Alvarez developed text-based similarity algorithms for the UN World Food Programme to support cash-based relief delivery.

Man in Bangladesh wearing a face mask

In recent weeks, Prof. Joshua Blumenstock has worked with policymakers in Togo, Nigeria, and Bangladesh to focus the power of advanced technology on pandemic relief.

Aditya Parameswaran

Assistant Professor Aditya Parameswaran has been awarded the Best Paper Award at the 2020 ACM SIGMOD/PODS Conference for his joint paper: “ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines.”

Josh Blumenstock

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.

Hany Farid

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

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.

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