Anind K. Dey

Dean and Professor

University of Washington

United States

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About

Anind K. Dey is the Dean and Professor at the University of Washington, United States. His research primarily focuses on mobile sensing and its applications in behavioral health, including studies on college students' perceived unfair treatment and the detection of acute marijuana intoxication. He also explores digital phenotyping and machine learning to assess health outcomes, particularly related to multiple sclerosis and mental health during the COVID-19 pandemic.

Articles (15)

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2025

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2021

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2021

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2020

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2020

Collaborators (15)

Marzyeh Ghassemi

Massachusetts Institute of Technology

UNITED STATES

Anind K. Dey

Research Interests

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About

Articles (15)

Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation

Detecting Perceived Unfair Treatment among U.S. College Students Using Mobile Sensing: Pilot Machine Learning Study (Preprint)

Identifying Links Between Productivity and Biobehavioral Rhythms Modeled From Multimodal Sensor Streams: Exploratory Quantitative Study

Mental-LLM

Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study

Enhancing Interpretable, Transparent and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions (Preprint)

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

Exploratory machine learning modeling of adaptive and maladaptive personality traits from passively sensed behavior

Impact of Online Learning in the Context of COVID-19 on Undergraduates with Disabilities and Mental Health Concerns

Predicting Job Performance Using Mobile Sensing

Mobile phone sensor-based detection of subjective cannabis intoxication in young adults: A feasibility study in real-world settings

Understanding practices and needs of researchers in human state modeling by passive mobile sensing

Digital Biomarkers of Symptom Burden Self-Reported by Perioperative Patients Undergoing Pancreatic Surgery: Prospective Longitudinal Study

Mobile Assessment of Acute Effects of Marijuana on Cognitive Functioning in Young Adults: Observational Study

A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Usability and Feasibility Study

Collaborators (15)

Marzyeh Ghassemi

Krina Durica

Dakuo Wang

Sheldon Cohen

Sang Won Bae

Shruthi Venkatesh

Jennifer Brown

Koustuv Saha

Pino G. Audia

Jennifer Mankoff

Runze Yan

Mayank Goel

James Hendler

Xuhai Xu

Kelly Mack

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