most citedContextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App

59 citations · 88 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC202459 cited

Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App

Subigya Nepal, Arvind Pillai, William Campbell +11

MindScape aims to study the benefits of integrating time series behavioral patterns (e.g., conversational engagement, sleep, location) with Large Language Models (LLMs) to create a…

cs.HC202421 cited

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

Subigya Nepal, Arvind Pillai, Weichen Wang +9

MoodCapture presents a novel approach that assesses depression based on images automatically captured from the front-facing camera of smartphones as people go about their daily liv…

cs.HC2023

Social Isolation and Serious Mental Illness: The Role of Context-Aware Mobile Interventions

Subigya Nepal, Arvind Pillai, Emma M. Parrish +4

Social isolation is a common problem faced by individuals with serious mental illness (SMI), and current intervention approaches have limited effectiveness. This paper presents a b…

cs.LG20238 cited

Rare Life Event Detection via Mobile Sensing Using Multi-Task Learning

Arvind Pillai, Subigya Nepal, Andrew Campbell

Rare life events significantly impact mental health, and their detection in behavioral studies is a crucial step towards health-based interventions. We envision that mobile sensing…

cs.SD2023

Using Mobile Data and Deep Models to Assess Auditory Verbal Hallucinations

Shayan Mirjafari, Subigya Nepal, Weichen Wang +1

Hallucination is an apparent perception in the absence of real external sensory stimuli. An auditory hallucination is a perception of hearing sounds that are not real. A common for…