59 citations · 95 across the 16 of their papers we have counts for
21 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…
MontageFlow: Physically Valid High Fidelity EEG Generation
Sudarshan Regmi, Nabaraj Subedi, Arvind Pillai +6
Generative modeling offers a promising solution to the scarcity of labeled clinical electroencephalography (EEG) data under strict privacy constraints. Although recent generative m…
Lapras: Latent Reasoning for Time Series Language Models
Yuliang Chen, Yu Yvonne Wu, Patrick Langer +11
Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural language answers and explanatio…
TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models
Martin Maritsch, Timo Stoffregen, Thomas Kaar +36
Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…
TimeThink: Eliciting Compositional Reasoning in Timeseries Large Language Models
Sudarshan Regmi, Arvind Pillai, Yu Yvonne Wu +7
Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for question-answering tasks. Howev…
BALMS: Benchmarking Agentic LLMs for Longitudinal Mental Health Sensing
Yu Yvonne Wu, Arvind Pillai, Yuliang Chen +7
Mental health assessment relies on episodic self-report scales, which convert subjective states such as stress into numerical scores but provide only sparse snapshots of wellbeing.…
ReliaGate: Reliability Routing for Low-Stakes Wearable Stress Prediction
Jaden Moon, Yu Wu, Arvind Pillai +1
We study when a wearable stress system should surface a prediction rather than change it. In low-stakes reflection and summary settings, aggregate accuracy is insufficient because…
When Does Quality-Aware Multimodal Fusion Matter? A Leakage-Safe Diagnostic for Decision-Level Dependence
Jaden Moon, Arvind Pillai, Andrew Campbell
Many multimodal systems estimate the reliability of each modality and weight their contributions to the final prediction. However, it remains unclear whether these scores influence…
WavesFM: Hierarchical Representation Learning for Longitudinal Wearable Sensor Waveforms
Peng Cao, Zhijian Yang, Tennison Liu +17
Wearable sensors enable the continuous acquisition of high-resolution physiological waveforms, such as photoplethysmography and accelerometry, under free-living conditions. However…
Learning Transferable Sensor Models via Language-Informed Pretraining
Yuliang Chen, Arvind Pillai, Yu Yvonne Wu +6
Multimodal language models have demonstrated strong semantic understanding and reasoning over physiological and behavioral signals captured from diverse healthcare sensors. However…
MotionTeller: Multi-modal Integration of Wearable Time-Series with LLMs for Health and Behavioral Understanding
Aiwei Zhang, Arvind Pillai, Andrew Campbell +1
As wearable sensing becomes increasingly pervasive, a key challenge remains: how can we generate natural language summaries from raw physiological signals such as actigraphy - minu…
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…
PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar +1
Photoplethysmography (PPG) is the leading non-invasive technique for monitoring biosignals and cardiovascular health, with widespread adoption in both clinical settings and consume…
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…
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…
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…
Personalized Step Counting Using Wearable Sensors: A Domain Adapted LSTM Network Approach
Arvind Pillai, Halsey Lea, Faisal Khan +1
Activity monitors are widely used to measure various physical activities (PA) as an indicator of mobility, fitness and general health. Similarly, real-time monitoring of longitudin…