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Computer Science

D-Index
59
Citations
10633
World Ranking
3491
National Ranking
1680

Overview

James Fogarty is affiliated with the University of Washington in the United States. Their research primarily spans the field of Computer Science, with a focus on Human-Computer Interaction and Applied Psychology, alongside contributions to Demography, Artificial Intelligence, and Electrical and Electronic Engineering.

The main topics of their work include Innovative Human-Technology Interaction, Digital Mental Health Interventions, Technology Use by Older Adults, Green IT and Sustainability, Digital Accessibility for Disabilities, Behavioral Health and Interventions, and Persona Design and Applications.

Frequent coauthors in Fogarty's research include Sean A. Munson, Jacob O. Wobbrock, Ravi Karkar, Julie A. Kientz, and Mingyuan Zhong.

Fogarty has published multiple papers in a range of scholarly venues. The most common publication venues for their work are:

  • Proceedings of the ACM on Human-Computer Interaction
  • Journal of Choice Modelling
  • ACM Transactions on Accessible Computing
  • Frontiers in Digital Health
  • CHI Conference on Human Factors in Computing Systems

Notable recent papers authored by or with Fogarty include:

  • DreamCatcher: Exploring How Parents and School-Age Children can Track and Review Sleep Information Together, 2020, Proceedings of the ACM on Human-Computer Interaction
  • An Epidemiology-inspired Large-scale Analysis of Android App Accessibility, 2020, ACM Transactions on Accessible Computing
  • Parallel Journeys of Patients with Cancer and Depression: Challenges and Opportunities for Technology-Enabled Collaborative Care, 2020, Proceedings of the ACM on Human-Computer Interaction
  • R packages and tutorial for case 1 best-worst scaling, 2022, Journal of Choice Modelling
  • The Importance of Starting With Goals in N-of-1 Studies, 2020, Frontiers in Digital Health

Best Publications

  • A lived informatics model of personal informatics

    Daniel A. Epstein;An Ping;James Fogarty;Sean A. Munson

  • Predicting human interruptibility with sensors

    James Fogarty;Scott E. Hudson;Christopher G. Atkeson;Daniel Avrahami

  • Predicting human interruptibility with sensors: a Wizard of Oz feasibility study

    Scott Hudson;James Fogarty;Christopher Atkeson;Daniel Avrahami

  • Examining Menstrual Tracking to Inform the Design of Personal Informatics Tools

    Daniel A. Epstein;Nicole B. Lee;Jennifer H. Kang;Elena Agapie

  • Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition

    James Fogarty;Carolyn Au;Scott E. Hudson

  • Barriers and Negative Nudges: Exploring Challenges in Food Journaling

    Felicia Cordeiro;Daniel A. Epstein;Edison Thomaz;Elizabeth Bales

  • Beyond Abandonment to Next Steps: Understanding and Designing for Life after Personal Informatics Tool Use

    Daniel A. Epstein;Monica Caraway;Chuck Johnston;An Ping

  • HydroSense: infrastructure-mediated single-point sensing of whole-home water activity

    Jon E. Froehlich;Eric Larson;Tim Campbell;Conor Haggerty

  • Boundary Negotiating Artifacts in Personal Informatics: Patient-Provider Collaboration with Patient-Generated Data

    Chia-Fang Chung;Kristin Dew;Allison Cole;Jasmine Zia

  • CueFlik: interactive concept learning in image search

    James Fogarty;Desney Tan;Ashish Kapoor;Simon Winder

  • When Personal Tracking Becomes Social: Examining the Use of Instagram for Healthy Eating

    Chia-Fang Chung;Elena Agapie;Jessica Schroeder;Sonali Mishra

  • Presence versus availability: the design and evaluation of a context-aware communication client

    James Fogarty;Jennifer Lai;Jim Christensen

  • Taming data complexity in lifelogs: exploring visual cuts of personal informatics data

    Daniel Epstein;Felicia Cordeiro;Elizabeth Bales;James Fogarty

  • From Personal Informatics to Family Informatics: Understanding Family Practices around Health Monitoring

    Laura R. Pina;Sang-Wha Sien;Teresa Ward;Jason C. Yip

  • Examining the robustness of sensor-based statistical models of human interruptibility

    James Fogarty;Scott E. Hudson;Jennifer Lai

  • Rethinking the Mobile Food Journal: Exploring Opportunities for Lightweight Photo-Based Capture

    Felicia Cordeiro;Elizabeth Bales;Erin Cherry;James Fogarty

  • Regroup: interactive machine learning for on-demand group creation in social networks

    Saleema Amershi;James Fogarty;Daniel Weld

  • How it works: a field study of non-technical users interacting with an intelligent system

    Joe Tullio;Anind K. Dey;Jason Chalecki;James Fogarty

  • Assieme: finding and leveraging implicit references in a web search interface for programmers

    Raphael Hoffmann;James Fogarty;Daniel S. Weld

  • Prefab: implementing advanced behaviors using pixel-based reverse engineering of interface structure

    Morgan Dixon;James Fogarty

Frequent Co-Authors

Sean A. Munson
Sean A. Munson University of Washington
Scott E. Hudson
Scott E. Hudson Carnegie Mellon University
Julie A. Kientz
Julie A. Kientz University of Washington
Jacob O. Wobbrock
Jacob O. Wobbrock University of Washington
Desney S. Tan
Desney S. Tan Microsoft (United States)
Ashish Kapoor
Ashish Kapoor Microsoft (United States)
Jon E. Froehlich
Jon E. Froehlich University of Washington
Shwetak N. Patel
Shwetak N. Patel University of Washington
James A. Landay
James A. Landay Stanford University
Daniel S. Weld
Daniel S. Weld University of Washington

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