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Computer Science

D-Index
88
Citations
56749
World Ranking
658
National Ranking
349

Overview

Anind K. Dey is affiliated with the University of Washington in the United States. Their research spans multiple areas, primarily focusing on psychology and computer science, with significant contributions in subfields such as applied psychology, experimental and cognitive psychology, clinical psychology, artificial intelligence, and general health professions.

Their work explores several main topics, including mental health research, digital mental health interventions, and the impact of COVID-19 on mental health. Additional areas of research include mobile health and mHealth applications, green IT and sustainability, behavioral health and interventions, and machine learning in healthcare.

They have published extensively in a range of academic venues, with frequent contributions to arXiv (Cornell University), Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, bioRxiv (Cold Spring Harbor Laboratory), JMIR Perioperative Medicine, and JMIR Formative Research.

Recent notable papers include:

  • Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing, 2021, ACM Transactions on Computer-Human Interaction
  • Mental-LLM, 2024, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • GLOBEM, 2022, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • Leveraging Collaborative-Filtering for Personalized Behavior Modeling, 2021, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data, 2023, arXiv (Cornell University)

Their frequent co-authors are Jennifer Mankoff, Xuhai Xu, Afsaneh Doryab, Yasaman S. Sefidgar, and Michael Tumminia.

Best Publications

  • Understanding and Using Context

    Anind K. Dey

  • Towards a Better Understanding of Context and Context-Awareness

    Gregory D. Abowd;Anind K. Dey;Peter J. Brown;Nigel Davies

  • A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications

    Anind K. Dey;Gregory D. Abowd;Daniel Salber

  • Maximum entropy inverse reinforcement learning

    Brian D. Ziebart;Andrew Maas;J. Andrew Bagnell;Anind K. Dey

  • Providing architectural support for building context-aware applications

    Anind Kumar Dey;Gregory D. Abowd

  • The context toolkit: aiding the development of context-enabled applications

    Daniel Salber;Anind K. Dey;Gregory D. Abowd

  • Towards a Better Understanding of Context and Context-Awareness

    Unknown

  • A stage-based model of personal informatics systems

    Ian Li;Anind Dey;Jodi Forlizzi

  • Heuristic evaluation of ambient displays

    Jennifer Mankoff;Anind K. Dey;Gary Hsieh;Julie Kientz

  • Smart Devices are Different: Assessing and MitigatingMobile Sensing Heterogeneities for Activity Recognition

    Allan Stisen;Henrik Blunck;Sourav Bhattacharya;Thor Siiger Prentow

  • Location-Based Services for Mobile Telephony: a study of users' privacy concerns

    Louise Barkhuus;Anind K. Dey

  • Why and why not explanations improve the intelligibility of context-aware intelligent systems

    Brian Y. Lim;Anind K. Dey;Daniel Avrahami

  • Understanding my data, myself: supporting self-reflection with ubicomp technologies

    Ian Li;Anind K. Dey;Jodi Forlizzi

  • Planning-based prediction for pedestrians

    Brian D. Ziebart;Nathan Ratliff;Garratt Gallagher;Christoph Mertz

  • The Conference Assistant: combining context-awareness with wearable computing

    A.K. Dey;D. Salber;G.D. Abowd;M. Futakawa

  • CybreMinder: A Context-Aware System for Supporting Reminders

    Anind K. Dey;Gregory D. Abowd

  • A Context-Based Infrastructure for Smart Environments

    Anind K. Dey;Gregory D. Abowd;Daniel Salber

  • Psycho-physiological measures for assessing cognitive load

    Eija Haapalainen;SeungJun Kim;Jodi F. Forlizzi;Anind K. Dey

  • Principles of smart home control

    Scott Davidoff;Min Kyung Lee;Charles Yiu;John Zimmerman

  • Is Context-Aware Computing Taking Control away from the User? Three Levels of Interactivity Examined

    Louise Barkhuus;Anind K. Dey

  • AWARE: Mobile Context Instrumentation Framework

    Denzil Ferreira;Vassilis Kostakos;Anind K. Dey

Frequent Co-Authors

Jennifer Mankoff
Jennifer Mankoff University of Washington
Gregory D. Abowd
Gregory D. Abowd Northeastern University
Jodi Forlizzi
Jodi Forlizzi Carnegie Mellon University
Denzil Ferreira
Denzil Ferreira University of Oulu
J. Andrew Bagnell
J. Andrew Bagnell Carnegie Mellon University
Manuela Veloso
Manuela Veloso Carnegie Mellon University
Vassilis Kostakos
Vassilis Kostakos University of Melbourne
Sara Kiesler
Sara Kiesler Carnegie Mellon University
John Zimmerman
John Zimmerman Carnegie Mellon University
Andrew T. Campbell
Andrew T. Campbell Dartmouth College

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