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Media Coverage & Talks

My research on AI-driven mental health solutions has been featured in major media outlets and presented at leading academic conferences and industry venues, highlighting the broader impact and relevance of technology-assisted mental health research.

Conference Presentations & Invited Talks

Leveraging Digital Behavioral Signals for AI-powered Mental Health Assessment, Prediction, and Intervention

• University of Illinois Urbana-Champaign, Siebel School of Computing and Data Science (April 2025)

• Yale University, Center for Brain and Mind Health (April 2025)

• Stanford University, HCI Group (March 2025)

• University of Maryland, Department of Information Systems (March 2025)

• Virginia Tech, Department of Computer Science (March 2025)

• Penn State University, College of Information Sciences and Technology (March 2025)

• University of Virginia, Department of Computer Science (February 2025)

Burnout in Cybersecurity Incident Responders: Exploring the Factors that Light the Fire

CSCW’24, San José, Costa Rica

The Science of Digital Wellbeing: Challenges and Opportunities in Mobile Mental Health

Flourish Science, Inc., Palo Alto, CA (2024)

Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health

ACM IMWUT/UbiComp’24, Melbourne, Australia

Contextual AI Journaling

ACM CHI EA’24, Honolulu, Hawaii

MoodCapture: Depression Detection using In-the-Wild Smartphone Images

Digital Health Summit, Dartmouth College, NH (2023)

The Power of Speech in the Wild

ACM IMWUT/UbiComp’23, Cancún, Mexico

From User Surveys to Telemetry-Driven Agents: Exploring the Potential of Personalized Productivity Solutions

Microsoft Research (2023)

Workplace Rhythm Variability and Emotional Distress in Information Workers

ACM CHI EA’23, Hamburg, Germany

Burnout in Cybersecurity Incident Responders: Exploring the Factors that Light the Fire

Microsoft Research (2022)

COVID Student Study

ACM CHI’22, New Orleans, LA

COVID Student Study

Dartmouth Innovation and Technology Festival, Dartmouth College, NH (2022)

Differentiating Higher and Lower Job Performers in the Workplace using Mobile Sensing

ACM IMWUT/UbiComp’19, London, UK

Media Coverages

2025

In the Face of Depression

Feature Article

Dartmouth Alumni Magazine

May 2025 feature on depression detection research and AI mental health innovations

2024

Stanford HAI Website

Featured on Stanford HAI website for postdoctoral fellowship

Dartmouth News

Coverage of four-year mobile sensing study

Mobile App Predicts Depression by Reading Your Expression

Interview

The Ross Kaminsky Show (iHeartRadio) | The Times | Dartmouth News

Radio interview and news coverage of MoodCapture study

Microsoft Research Blog

Highlighted as notable publication on personalized productivity solutions

2023

Washington Post

Featured research on technology’s role in addressing youth mental health

Dartmouth CS News

Coverage of UbiComp Distinguished Paper Award

2022

Washington Post

Major coverage of COVID student study research

2021

Smartphone Intervention Feasible for Severe Mental Illness

Health News

HealthDay News | Verywell Mind | Psychiatric News

Coverage of mobile intervention study for serious mental illness

Dartmouth News

Coverage of commuting impact on workplace performance research

Rates of Anxiety and Depression Among College Students Continue to Soar

Research Coverage

Washington Post | Union Leader

Coverage of college student mental health research

Tuck News

Business school coverage of workplace sensing research

2020

Washington Post | The GW Hatchet

Early pandemic impact on college student mental health

2019

Researchers Developed a Sensing System to Constantly Track Worker Performance

Tech Coverage

TechCrunch | Washington Post | Financial Times | Boston Globe | Bloomberg

Widespread coverage of workplace performance sensing research

Impact & Reach

Research presented at leading venues including CHI, UbiComp, and CSCW, and featured in Washington Post, Financial Times, TechCrunch, Bloomberg, reaching millions worldwide and highlighting the societal relevance of AI-driven mental health research.