Publications

Mapping the global ocean-atmosphere boundary layer with a SAR satellite foundation model

Glaser et al. — Remote Sensing of Environment, 2026. In preparation

A deep learning foundation model for dual-energy X-ray absorptiometry imaging

Glaser et al. — Radiology, 2026. In preparation

WV-Net: A foundation model for SAR ocean satellite imagery

Glaser et al. — AI for the Earth Systems, AMS, 2025.

SPIn4D I: Overview, MHD modeling, and Stokes profile synthesis

Yang, ..., Glaser et al. — Astrophysical Journal 976(2):204, 2024.

Is AI-enhanced breast ultrasound ready for screening in low-resource environments? A systematic review

Bunnell, ..., Glaser et al. — Cancer Research 84(6_Suppl):3449, 2024.

Generative deep learning furthers understanding of fat/muscle distributions using 3D surface scans

Leong, ..., Glaser et al. — Communications Medicine 4(1):13, 2024.

Diffusion models for high-resolution solar forecasts

Hatanaka, Glaser et al. — arXiv:2302.00170, 2023.

Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging

Glaser et al. — Communications Medicine 2(1):102, 2022.

Evolution of left–right asymmetry in sensory system and foraging behavior in cave fish

Fernandes, Glaser et al. — BMC Biology 20(1):295, 2022.

Deep learning for predicting significant wave height from SAR

Quach, Glaser et al. — IEEE TGRS 59(3):1859–1867, 2020.

Domain-Specific Foundation Models for Science Applications: Self-Supervised Learning with SAR and DXA

Glaser et al. — MICCAI Doctoral Symposium, 2025.

Learning a clinically-relevant concept bottleneck for lesion detection in breast ultrasound

Bunnell, Glaser et al. — MICCAI, pp. 650–659, 2024.

Evolution-informed neural networks for microbiome data analysis

Ito, Glaser, Sadowski — IEEE BIBM, pp. 3386–3391, 2021.

Deep sensing of ocean wave heights with SAR

Quach, Glaser, Stopa, Sadowski — AAAI Spring Symposium, 2020.

Hip fracture risk modeling using DXA and deep learning

Glaser et al. — NeurIPS ML & Physical Sciences Workshop, 2019.

Refined redshift regression in cosmology with graph convolution networks

Beck, Sadowski, Glaser, Szapudi — NeurIPS ML & Physical Sciences Workshop, 2019.