Alejandro Calle-Saldarriaga

Alejandro Calle-Saldarriaga

5th year Statistics PhD candidate working at the interface of Bayesian modeling and deep learning for large-scale scientific data: scalable Gaussian processes, deep generative models, and uncertainty quantification, mostly for climate and atmospheric problems. Graduating in 2027 and looking for jobs.

Publications

Generative multi-scale modeling via spatial autoregressive transport maps

Published in Technometrics, 2026

A multi-scale Bayesian transport map model for generative modeling of nonstationary spatial fields.

Recommended citation: Calle-Saldarriaga, A.; Wiemann, P.F.V.; Katzfuss, M. (2026). "Generative multi-scale modeling via spatial autoregressive transport maps." Technometrics.

Amortized probabilistic retrieval of atmospheric CO2 from OCO-2 spectra using deep learning with Laplace approximations and normalizing flows

Published in Preprint (under review), 2026

An amortized neural inference framework for calibrated, non-Gaussian uncertainty in satellite CO2 retrieval. Preprint, under review.

Recommended citation: Calle-Saldarriaga, A.; Jimenez, F.; Grosskreuz, J.; Wang, J.; Hobbs, J.; Katzfuss, M. (2026). "Amortized probabilistic retrieval of atmospheric CO2 from OCO-2 spectra using deep learning with Laplace approximations and normalizing flows." Preprint, under review. https://arxiv.org/abs/2606.17413