most citedMIND: Empowering Mental Health Clinicians with Multimodal Data Insights through a Narrative Dashboard

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Learning Behavioral Signals from Encrypted Smartphone Network Traffic

Rameen Mahmood, Omar El Shahawy, Souptik Barua +5

Human behavior is challenging to measure continuously at scale, yet traces of daily routines and well-being may be reflected in interactions with personal devices. We investigate w…

cs.AI2026

Towards a General Intelligence and Interface for Wearable Health Data

Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37

While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…

cs.LG2026

TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health

Yuang Fan, Lilin Xu, Millie Wu +8

Longitudinal passive sensing enables continuous health prediction, yet models often fail under cross-dataset distribution shifts. Traditional ML overfits cohort-specific artifacts,…

cs.HC20261 cited

MIND: Empowering Mental Health Clinicians with Multimodal Data Insights through a Narrative Dashboard

Ruishi Zou, Shiyu Xu, Margaret E Morris +11

Advances in data collection enable the capture of rich patient-generated data: from passive sensing (e.g., wearables and smartphones) to active self-reports (e.g., cross-sectional…

cs.AI2025

The Anatomy of a Personal Health Agent

A. Ali Heydari, Ken Gu, Vidya Srinivas +35

Health is a fundamental pillar of human wellness, and the rapid advancements in large language models (LLMs) have driven the development of a new generation of health agents. Howev…