Nino-Ruiz, E.D., \& Valbuena, S.R. (2022). TEDA: A Computational Toolbox for Teaching Ensemble Based Data Assimilation. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13353. Springer, Cham.
Nino-Ruiz, E. D., \& Acevedo García, F. J. (2021, June). Data-Driven Methods for Weather Forecast. In International Conference on Computational Science (pp. 326-336). Springer, Cham.
Nino-Ruiz, E. D. (2020, June). A Random Line-Search Optimization Method via Modified Cholesky Decomposition for Non-linear Data Assimilation. In International Conference on Computational Science (pp. 189-202). Springer, Cham.
Tellez, N., Jimeno, M., Salazar, A., & Nino-Ruiz, E. D. (2019, November). Container-based architecture for optimal face-recognition tasks in edge computing. In Proceedings of the 4th ACM/IEEE Symposium on Edge Computing (pp. 301-303).
Nino-Ruiz, E. D., Mancilla-Herrera, A. M., & Beltran-Arrieta, R. (2018, May). Non-Gaussian data assimilation via modified cholesky decomposition. In 2018 7th International Conference on Computers Communications and Control (ICCCC) (pp. 29-36). IEEE.
Nino-Ruiz, E. D., Ardila, C. J., Mancilla, A., & Estrada, J. (2017). A Surrogate Model Based On Mixtures Of Taylor Expansions For Trust Region Based Methods. Procedia Computer Science, 108, 1473-1482.
Nino-Ruiz, E. D., Mancilla, A., & Calabria, J. C. (2017). A posterior ensemble kalman filter based on a modified cholesky decomposition. Procedia Computer Science, 108, 2049-2058.
Guzman, L. G., Ruiz, E. N., Ardila, C. J., Jabba, D., & Nieto, W. (2016, May). A novel framework for the parallel solution of combinatorial problems implementing tabu search and simulated annealing algorithms. In 2016 6th International Conference on Computers Communications and Control (ICCCC) (pp. 259-263). IEEE.
Nino-Ruiz, E. D., & Sandu, A. (2015, December). An efficient parallel implementation of the ensemble Kalman filter based on shrinkage covariance matrix estimation. In Proceedings of the 2015 IEEE 22nd International Conference on High Performance Computing Workshops (HiPCW) (pp. 54-54).
Nino-Ruiz, E. D., Sandu, A., & Deng, X. (2015, November). A parallel ensemble Kalman filter implementation based on modified Cholesky decomposition. In Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (pp. 1-8).
Nino-Ruiz, E. D., Sandu, A., & Deng, X. (2015, November). A parallel ensemble Kalman filter implementation based on modified Cholesky decomposition. In Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (pp. 1-8).
Nino, E. D., & Sandu, A. (2014, November). Variational Data Assimilation Based on Derivative-Free Optimization. In International Conference on Dynamic Data-Driven Environmental Systems Science (pp. 239-250). Springer, Cham.
Sandu, A., Ştefănescu, R., Rao, V., & Nino, E. (2014). The use of reduced order models in the solution of inverse problems. Blucher Material Science Proceedings, 1(1), 24-24.