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

Summer and Fall 2020 MIDS and MICS Award Winners

Feb 3, 2021

Outstanding MICS and MIDS capstone projects, and distinguished teaching awards.

Data For Good Fellowship Recipient Wants to Empower Rural Healthcare Providers with AI

Jan 21, 2021

Mahdieh Taher (MIDS ’20) has been awarded the Jack Larson Data for Good Fellowship for her work as a data engineer dedicated to improving medical diagnoses in rural areas.

Blumenstock’s Research Brings Cash Aid to to Togo’s Poorest

Dec 11, 2020

Charity Worked with Josh Blumenstock to Identify Aid Recipients in Togo Using Mobile Phone Data

Dec 11, 2020

Jennifer Chayes at NeurIPS ’20: ML Community Must Work With Interdisciplinary Experts

Dec 14, 2020

Prof. Blumenstock’s Technology Brings Covid Aid to Togo

Dec 17, 2020

Pioneering NLP Research Examines Representation in Texas Textbooks

Oct 28, 2020

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

Ph.D. Student Doris Lee Awarded 2020 Facebook Fellowship in Systems for Machine Learning

Sep 11, 2020

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

David Bamman Wins National Endowment for Humanities Grant

Aug 13, 2020

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.

Berkeley Student Develops Text-Based ID Strategies to Support UN’s Cash Assistance Programs

Jul 28, 2020

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