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 a 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 two areas:

AI for Mental Health: I develop models from different modalities to evaluate the presence of mental illness symptoms: (a) rare life events for sensor data [CHIL’23], (b) suicidal ideation detection from speech [UbiComp’24], and (c) depression detection from front-facing smartphone images [CHI’24].
ML Generalizability: I am interested in analyzing the generalizability of healthcare ML models. To this end, I developed an open foundation model for PPG data that is evaluated on 10 different datasets with varying real-world conditions [ICLR’25]. I have also proposed a domain adaptation method and investigated the generalization of speech-based suicidal ideation detection [UbiComp’24].

news

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

Selected Publications

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

Awareded Bib PDF Video Code

Best Paper Award at the NeurIPS Time Series in the Age Large Models Workshop

@article{pillai2024papagei,
  title = {PaPaGei: Open Foundation Models for Optical Physiological Signals},
  author = {Pillai, Arvind and Spathis, Dimitris and Kawsar, Fahim and Malekzadeh, Mohammad},
  journal = {In International Conference on Learning Representations},
  year = {2025},
  models = {https://zenodo.org/records/13983110},
  selected = true,
}

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

Bib PDF Video

@inproceedings{nepal2024moodcapture,
  title = {MoodCapture: Depression Detection Using In-the-Wild Smartphone Images},
  author = {Nepal*, Subigya and Pillai*, Arvind and Wang, Weichen and Griffin, Tess and Collins, Amanda C and Heinz, Michael and Lekkas, Damien and Mirjafari, Shayan and Nemesure, Matthew and Price, George and others},
  booktitle = {Proceedings of the CHI Conference on Human Factors in Computing Systems},
  pages = {1--18},
  year = {2024},
}

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

Bib PDF

@article{pillai2024investigating,
  title = {Investigating Generalizability of Speech-based Suicidal Ideation Detection Using Mobile Phones},
  author = {Pillai, Arvind and Nepal, Subigya Kumar and Wang, Weichen and Nemesure, Matthew and Heinz, Michael and Price, George and Lekkas, Damien and Collins, Amanda C and Griffin, Tess and Buck, Benjamin and others},
  journal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
  volume = {7},
  number = {4},
  pages = {1--38},
  year = {2024},
  publisher = {ACM New York, NY, USA},
}

CHIL

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

Arvind Pillai, Subigya Nepal, and Andrew Campbell

In Conference on Health, Inference, and Learning , 2023

Bib PDF

@inproceedings{pillai2023rare,
  title = {Rare Life Event Detection via Mobile Sensing Using Multi-Task Learning},
  author = {Pillai, Arvind and Nepal, Subigya and Campbell, Andrew},
  booktitle = {Conference on Health, Inference, and Learning},
  pages = {279--293},
  year = {2023},
  organization = {PMLR},
}