Wang shares smart home privacy, inclusive privacy at NSF meeting

Yang Wang
Yang Wang, Associate Professor

Associate Professor Yang Wang will share his work at the National Science Foundation (NSF) Secure and Trustworthy Cyberspace (SaTC) Principal Investigators' Meeting, which will be held on October 28-29 in Washington, D.C. He will share his research from two SaTC-funded projects.

The first project focuses on Privacy-Enhancing User Interfaces Based on Individualized Mental Models. While smart home devices are designed to make life easier, these devices come with the risk that developers will use the collected data at the expense of user privacy.

"In our project, we present the design and evaluation of machine learning models that predict personalized allow/deny decisions for different information flows involving various attributes, purposes, and devices; what circumstances may change original decisions; and how much money one may be willing to pay or receive in exchange for smart home privacy," Wang said. "We show how developers can use our models to derive actionable steps toward privacy-preserving data practices in the smart home."

The second project focuses on Inclusive Privacy: Effective Privacy Management for People with Visual Impairments. To better inform privacy/security designs for people with visual impairments, Wang's research group "shadowed" people with these impairments and their allies, such as friends, family members, and professional helpers. They found that people with visual impairments often work closely with their allies to protect their privacy and security. According to Wang, there is particularly "a need for designing mechanisms or tools that facilitate cooperative privacy management."

Wang, who joined the iSchool faculty in August, conducts research focusing on usable privacy and security technologies, social computing, human-computer interaction, and explainable artificial intelligence. His research has received support from NSF, the Department of Health and Human Services, Google, Alcatel-Lucent, and The Privacy Projects, and has appeared in news outlets such as The New York Times, The Wall Street Journal, BBC, and China Daily. Wang's honors include the IAPP SOUPS Privacy Award, NSF CAREER Award, and a Top Privacy Paper for Policy Makers selected by the Future of Privacy Forum. He earned his PhD in information and computer science from the University of California, Irvine.

Updated on
Backto the news archive

Related News

Trainor receives the Karen Wold Level the Learning Field Award

Senior Lecturer Kevin Trainor has been selected by the Division of Disability Resources and Educational Services (DRES) to receive the 2024 Karen Wold Level the Learning Field Award. This award honors exemplary members of faculty and staff for advocating and/or implementing instructional strategies, technologies, and disability-related accommodations that afford students with disabilities equal access to academic resources and curricula. 

Kevin Trainor

Seo coauthors chapter on data science and accessibility

Assistant Professor JooYoung Seo and Mine Dogucu, professor of statistics in the Donald Bren School of Information and Computer Sciences at the University of California Irvine, have coauthored a chapter in the new book Teaching Accessible Computing. The goal of the book, which is edited by Alannah Oleson, Amy J. Ko and Richard Ladner, is to help educators feel confident in introducing topics related to disability and accessible computing and integrating accessibility into their courses.

JooYoung Seo

iSchool instructors ranked as excellent

Fifty-five iSchool instructors were named in the University's List of Teachers Ranked as Excellent for Fall 2023. The rankings are released every semester, and results are based on the Instructor and Course Evaluation System (ICES) questionnaire forms maintained by Measurement and Evaluation in the Center for Innovation in Teaching and Learning. 

iSchool Building

ConnectED: Tech for All podcast launched by Community Data Clinic

The Community Data Clinic (CDC), a mixed methods data studies and interdisciplinary community research lab led by Associate Professor Anita Say Chan, has released the first episode of its new podcast, ConnectED: Tech for All. Community partners on the podcast include the Housing Authority of Champaign County, Champaign-Urbana Public Health District, Project Success of Vermilion County, and Cunningham Township Supervisor’s Office.

Community Data Clinic podcast logo

New study shows LLMs respond differently based on user’s motivation

A new study conducted by PhD student Michelle Bak and Assistant Professor Jessie Chin, which was recently published in the Journal of the American Medical Informatics Association (JAMIA), reveals how large language models (LLMs) respond to different motivational states. In their evaluation of three LLM-based generative conversational agents (GAs)—ChatGPT, Google Bard, and Llama 2—the researchers found that while GAs are able to identify users' motivation states and provide relevant information when individuals have established goals, they are less likely to provide guidance when the users are hesitant or ambivalent about changing their behavior.