Arvind Pillai

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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:

  1. 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].

  2. 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].

  3. 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!
Jan 22, 2025 :parrot: PaPaGei is accepted to ICLR 2025!
Dec 15, 2024 :parrot: PaPaGei wins the :trophy: Best Paper Award at the Time Series in the Age of Large Models workshop at NeurIPS 2024.
Oct 29, 2024 :parrot: PaPaGei, a foundation model for PPG data is now available! Paper, Models, and Code
Oct 08, 2024 :microphone: Presented “Investigating Generalizability of Speech-Based Suicidal Ideation Detection Using Mobile Phones” @ Ubicomp 2024
Jun 01, 2024 :bell: I will be interning at Nokia Bell Labs in Cambridge, UK for Summer 2024
May 14, 2024 :microphone: Presented our work MoodCapture at CHI 2024 in Honolulu

Selected Publications

  1. CHIL
    Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting
    Arvind Pillai, Dimitris Spathis, Subigya Nepal, and 6 more authors
    Conference on Health, Inference, and Learning, 2025
  2. ICLR
    PaPaGei: Open Foundation Models for Optical Physiological Signals
    Arvind Pillai, Dimitris Spathis, Fahim Kawsar, and 1 more author
    In International Conference on Learning Representations, 2025
  3. CHI
    MoodCapture: Depression Detection Using In-the-Wild Smartphone Images
    Subigya Nepal*, Arvind Pillai*, Weichen Wang, and 8 more authors
    In Proceedings of the CHI Conference on Human Factors in Computing Systems , 2024
  4. UbiComp
    Investigating Generalizability of Speech-based Suicidal Ideation Detection Using Mobile Phones
    Arvind Pillai, Subigya Kumar Nepal, Weichen Wang, and 8 more authors
    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2024