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 Computer Science)

Data management, interactive or human-in-the-loop data analytics, information visualization, crowdsourcing, data science

Recent Publications

Differential Privacy for Black-Box Statistical Analyses

May 22, 2023

Monkeypox Outbreak Analysis: An Extensive Study Using Machine Learning Models and Time Series Analysis

Mar 30, 2023

Survivability of industrial internet of things using machine learning and smart contracts

Mar 1, 2023

SDN and application layer DDoS attacks detection in IoT devices by attention‐based Bi‐LSTM‐CNN

Mar 1, 2023

A transfer learning approach for detecting offensive and hate speech on social media platforms

Feb 2, 2023

Time series analysis and anomaly detection for trustworthy smart homes

Sep 11, 2022

Exchange and the Creation of Trust and Solidarity across Cultures

Sep 6, 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

Data Science news

School of Information Hiring New Professor in Human-Centered Data Science

Oct 8, 2015

Position will begin July 2016; applications are due December 14.

New Professor David Bamman is a Scholar of Computational Humanities and Social Sciences

Sep 1, 2015

Bamman’s work applies natural language processing and machine learning techniques to empirical questions in the humanities and social sciences.

School of Information Releases First-of-its-Kind Synchronized Brainwave Research Dataset

Mar 18, 2015

The dataset could help answer whether it’s possible to accurately use consumer-grade devices to interpret attention level in a problem-solving test. The class hopes that other researchers will be able to repeat the experiment with even larger subject pools.

Experts Mine Questions of Big Data, Power, and Privacy

Apr 3, 2014

Capped by a keynote from Obama adviser John Podesta, a day-long workshop brought together the worlds of government, business, the law, and academia for what assistant professor Deirdre Mulligan called “a frank and honest conversation about our values,” and about how to balance those values with the omnipresent, often invisible collection of data about every aspect of our lives.

Data Science Master's Degree Kicks Off to Fill Growing Need Across Industries

Jan 23, 2014

The School of Information has officially started its new online Master of Information and Data Science (MIDS) program, preparing students to solve real-world problems using complex and unstructured data.

Students’ Data Analysis Uncovers Hidden Trends in Yelp Reviews

Oct 4, 2013

A new student research project analyzes the text of Yelp restaurant reviews to automatically reveal the underlying topics discussed by the reviewers — and predict the rating the restaurant would have received based on each individual topic.

Zachary Pardos, Scholar of Online Education, Joins I School Faculty

Oct 15, 2013

Pardos is an expert in the emerging field of educational data mining — applying data science methodologies to online learning environments to understand student learning.