activity
20242026
most citedClinical ModernBERT: An efficient and long context encoder for biomedical text

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning

Hao Zhou, Simon A. Lee, Cyrus Tanade +12

Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, most existing self supervised…

cs.LG2026

Wavelet-Driven Masked Multiscale Reconstruction for PPG Foundation Models

Megha Thukral, Cyrus Tanade, Simon A. Lee +10

Wearable foundation models have the potential to transform digital health by learning transferable representations from large-scale biosignals collected in everyday settings. While…

cs.LG2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90

The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…

cs.LG2025

HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series

Simon A. Lee, Cyrus Tanade, Hao Zhou +13

Wearable sensors provide abundant physiological time series, yet the principles governing their predictive utility remain unclear. We hypothesize that temporal resolution is a fund…

cs.LG2024

FEET: A Framework for Evaluating Embedding Techniques

Simon A. Lee, John Lee, Jeffrey N. Chiang

In this study, we introduce FEET, a standardized protocol designed to guide the development and benchmarking of foundation models. While numerous benchmark datasets exist for evalu…