Publications

Below is a selected list of publications related to the Global Oculomics Initiative, spanning segmentation, distance prediction, foundational model development, and global deployment infrastructure. Preprints and manuscripts under review are included where appropriate.

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Nahass et al., TMLR (2025)

Nahass, G. R., Wang, Z., Rashidisabet, H., Kim, W. H., Hubschman, S., Peterson, J. C., ... & Ravi, S. N.
Targeted Unlearning Using Perturbed Sign Gradient Methods with Applications on Medical Images.
Transactions on Machine Learning Research (to appear 01/12/2025).
arXiv:2505.21872.

Nahass et al., Ophthalmology Science (2025)

Nahass, G. R., Koehler, E., Tomaras, N., Lopez, D., Cheung, M., Palacios, A., ... & Setabutr, P.
Open-Source Periorbital Segmentation Dataset for Ophthalmic Applications.
Ophthalmology Science, 100757.

Peterson et al., Ophthalmology Science (2025)

Peterson, J. C., Nahass, G. R., Lasalle, C., Bradley, D., Wu, D., Zorra, I., ... & Tran, A. Q.
Development and Validation of a Semi-Automated Tool for Measuring Periorbital Distances.
Ophthalmology Science, 100887.

Nahass et al., JMIR Human Factors (under review)

Nahass, G. R., van der Ende, J., Hubschman, S., Beltran, B., Kolli, B., Berek, C., … Tran, A. Q.
Glorbit: A Modular, Web-Based Platform for AI-Based Periorbital Measurement in Low-Resource Settings.
arXiv preprint. Under review at JMIR Human Factors.

Nahass et al., TVST (submitted)

Nahass, G. R., Hubschman, S., Peterson, J. C., Yazdanpanah, G., Tomaras, N., Cheung, M., ... & Yi, D.
State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features.
arXiv:2409.18769. Submitted to TVST.

Nahass et al., AJO International (2024)

Nahass, G. R., Peterson, J. C., Heinze, K., Choudhary, A., Khandwala, N., Purnell, C. A., ... & Tran, A. Q.
FaceFinder: A machine learning tool for identification of facial images from heterogeneous datasets.
AJO International, 1(4), 100083.