59 citations · 90 across the 14 of their papers we have counts for
19 papers
Scaling Therapy Supervision: Assessing Psychotherapy Fidelity Using Large Language Models
Arvind Pillai, Alexis Roach, Jason Holden +11
Psychotherapy fidelity assessment measures how faithfully a therapist adheres to a treatment protocol, a critical determinant of positive patient outcomes. However, fidelity assess…
What do AI chatbots do after users decline therapeutic redirection for suicide thoughts?
Subigya Nepal, Ruth Heo, Emma M Parrish +1
Safety evaluations of artificial intelligence (AI) chatbots focus on therapeutic redirection, statements urging users who disclose suicide thoughts to seek help from crisis lines o…
Faithful Where It Can Be Checked: Auditing a Reflection Agent Against Its System Prompt in a Randomized Trial
Subigya K. Nepal, Serena Soh, Noah Vinoya +3
Conversational agents are increasingly used to guide reflection. A recent randomized trial compared a GPT-4o career reflection agent with the same program in a static journaling su…
Cyber Exodus: Burnout Symptoms, Exit Intention, and Peer Response in Online Cybersecurity Communities
Nadia Mehjabin, Ji Hyun Kim, Laura Barnes +3
Security practitioners burn out at high rates, and the resulting attrition is itself a security problem. This workforce is hard to study: security operations centers are closed to…
Not All Nudges Land: Behavioral Controllability and Elaboration Quality in AI-Supported Journaling
Nadia Mehjabin, Henry Kautz, Subigya Nepal
AI journaling tools can tailor prompts to a person's own sensed behavior, but it is unclear which behaviors respond to them. We analyzed 369 journal entries from an eight-week pass…
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,…
The Structure and Dynamics of the Online MAHA-sphere
Sabit Ahmed, Subigya Nepal, Henry Kautz
The "Make America Healthy Again" (MAHA) movement has created a complex ideological ecosystem within online communities, where advocacy for healthier lifestyles and whole-food diets…
Causal Stories from Sensor Traces: Auditing Epistemic Overreach in LLM-Generated Personal Sensing Explanations
Shanshan Zhu, Han Zhang, J. Doris Chi +2
LLMs are increasingly used to explain personal sensing data, translating traces of activity and mood into natural-language accounts of why an anomalous day may have occurred. Howev…
PULSE: Agentic Investigation with Passive Sensing for Proactive Affective Intervention in Cancer Survivorship
Zhiyuan Wang, Subigya Nepal, Ariful Islam +5
Cancer survivors face elevated rates of depression, anxiety, and emotional distress, yet self-report may be unavailable at some moments when support is relevant, a challenge we ter…
LENS: LLM-Enabled Narrative Synthesis for Mental Health by Aligning Multimodal Sensing with Language Models
Wenxuan Xu, Arvind Pillai, Subigya Nepal +6
Multimodal health sensing offers rich behavioral signals for assessing mental health, yet translating these numerical time-series measurements into natural language remains challen…
Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting
Arvind Pillai, Dimitris Spathis, Subigya Nepal +6
Large language models (LLMs) show promise for health applications when combined with behavioral sensing data. Traditional approaches convert sensor data into text prompts, but this…
MindScape Study: Integrating LLM and Behavioral Sensing for Personalized AI-Driven Journaling Experiences
Subigya Nepal, Arvind Pillai, William Campbell +14
Mental health concerns are prevalent among college students, highlighting the need for effective interventions that promote self-awareness and holistic well-being. MindScape pionee…
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…
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…
From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions
Subigya Nepal, Javier Hernandez, Talie Massachi +7
Information workers increasingly struggle with productivity challenges in modern workplaces, facing difficulties in managing time and effectively utilizing workplace analytics data…
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…
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…
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…
A Survey of Passive Sensing for Workplace Wellbeing and Productivity
Subigya K. Nepal, Gonzalo J. Martinez, Arvind Pillai +9
The modern workplace is undergoing a radical transformation, driven by technological advances that blur the boundaries between human capability and digital augmentation. At the for…