Arvind Pillai

I am a 4th year PhD student at Dartmouth College, advised by Prof. Andrew Campbell. Previously, I was a research intern at Nokia Bell Labs (Cambridge, UK) (Summer 2024), and an AI & Data Graduate Scientist at AstraZeneca (2019-2021).
My interdisciplinary research centers on developing machine learning techniques to study health in real-world settings, utilizing data from wearable devices and mobile phone sensors. In particular, I am interested in these areas:
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Health Foundation Models: Developing models that can generalize to many tasks is crucial for healthcare. To this end, I have developed PaPaGei, which is the first open-source foundation model for Photoplethysmography (PPG) [ICLR’25]; And proposed Time2Lang, which is a framework to integrate time-series foundation models with LLMs [CHIL’25].
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Un/Semi-supervised Learning: I developed a method to detect rare life events from multi-modal sensing data [CHIL’23]. Additionally, I have also proposed a domain adaptation method and investigated the generalization of speech-based suicidal ideation detection [UbiComp’24a].
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Behavior Modelling using Mobile Systems: I develop machine learning models and contribute to mobile systems targeted at understanding mental health. In this area, I have developed models for depression detection from in-the-wild smartphone images [CHI’24], an intervention system for improving social interactions in individuals with schizophrenia [IEEE PerCom Magazine’24], and maintain large-scale datasets with over 3 years of continuous sensing data [UbiComp’24b].
news
Apr 09, 2025 | Delighted to share that Time2Lang is accepted to CHIL’25! |
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Jan 22, 2025 |
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Dec 15, 2024 |
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Oct 29, 2024 |
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May 14, 2024 |
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