A Sampling Approach for Four Dimensional Data Assimilation. - Ahmed Attia; Vishwas Rao; Adrian Sandu (DyDESS, 2014)

A Sampling Filter for Non-Gaussian Data Assimilation. - Ahmed Attia; Adrian Sandu (CoRR, 2014)

A Hybrid Monte-Carlo Sampling Smoother for Four Dimensional Data Assimilation. - Ahmed Attia; Vishwas Rao; Adrian Sandu (CoRR, 2015)

Cluster Sampling Filters for Non-Gaussian Data Assimilation. - Ahmed Attia; Azam S. Zavar Moosavi; Adrian Sandu (CoRR, 2016)

The Reduced-Order Hybrid Monte Carlo Sampling Smoother. - Ahmed Attia; Razvan Stefanescu; Adrian Sandu (CoRR, 2016)

DATeS: A Highly-Extensible Data Assimilation Testing Suite. - Ahmed Attia; Adrian Sandu (CoRR, 2017)

A Machine Learning Approach to Adaptive Covariance Localization. - Azam S. Zavar Moosavi; Ahmed Attia; Adrian Sandu (CoRR, 2018)

Goal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems. - Ahmed Attia; Alen Alexanderian; Arvind K. Saibaba (CoRR, 2018)

An Optimal Experimental Design Framework for Adaptive Inflation and Covariance Localization for Ensemble Filters. - Ahmed Attia; Emil M. Constantinescu (CoRR, 2018)

Tuning Covariance Localization Using Machine Learning. - Azam S. Zavar Moosavi; Ahmed Attia; Adrian Sandu (ICCS (4), 2019)

Brain-in-Car: A Brain Activity-based Emotion Recognition Embedded System for Automotive. - Abdelrahman El-Amin; Seif Eldawlatly; Ahmed Attia; Omar Hammad; Osama Nasr; Osama Ghozlan; Remon Raouf; Ahmed M. Hamed; Hany Eldawlatly; Magdy A. El-Moursy (ICVES, 2019)

Stochastic Learning Approach to Binary Optimization for Optimal Design of Experiments. - Ahmed Attia; Sven Leyffer; Todd S. Munson (CoRR, 2021)

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments. - Ahmed Attia; Sven Leyffer; Todd S. Munson (SIAM J. Sci. Comput., 2022)

Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations. - Ahmed Attia; Emil M. Constantinescu (SIAM J. Sci. Comput., 2022)

PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments. - Ahmed Attia; Shady E. Ahmed (CoRR, 2023)

Robust A-Optimal Experimental Design for Bayesian Inverse Problems. - Ahmed Attia; Sven Leyffer; Todd S. Munson (CoRR, 2023)

Centralized calibration of power system dynamic models using variational data assimilation. - Ahmed Attia; Daniel Adrian Maldonado; Emil M. Constantinescu; Mihai Anitescu (CoRR, 2023)

Probabilistic Approach to Black-Box Binary Optimization with Budget Constraints: Application to Sensor Placement. - Ahmed Attia (CoRR, 2024)

Robust optimal design of large-scale Bayesian nonlinear inverse problems. - Abhijit Chowdhary; Ahmed Attia; Alen Alexanderian (CoRR, 2024)

PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments. - Abhijit Chowdhary; Shady E. Ahmed; Ahmed Attia (ACM Trans. Math. Softw., 2024)

Robust A-Optimal Experimental Design for Sensor Placement in Bayesian Linear Inverse Problems. - Ahmed Attia; Sven Leyffer; Todd S. Munson (SIAM/ASA J. Uncertain. Quantification, 2025)