Elias D. Nino-Ruiz, Ph.D.

Associate Professor, Chair
Department of Computer Science
Universidad del Norte
Barranquilla 080001, Colombia.
Email: enino@uninorte.edu.co


Education:

  1. Ph.D. in Computer Science and Applications, Virginia Tech, USA. December 2015. Dissertation: Efficient Implementation of Ensemble-Based Methods in Data Assimilation.
  2. M.S. in Industrial Engineering. Universidad del Norte, Colombia. (ABET accredited institution) April 2010.
  3. M.S. in System Engineering and Computer Science, Colombia. Universidad del Norte (ABET accredited institution) May 2009
  4. B.S. in System Engineering. Universidad del Norte, Colombia. (ABET accredited institution) March 2007
Research Interests:
  1. Data Assimilation.
  2. Covariance Matrix Estimation.
  3. Inverse Problems.
  4. High Performance Computing.
  5. Numerical Optimization

Teaching:

Graduate-Level Courses:

  1. Optimization Theory, Universidad del Norte, Colombia (Spring 2019) - Course website
  2. Optimization Theory, Universidad del Norte, Colombia (Fall 2018) - Course website
  3. Data Assimilation, Universidad del Norte, Colombia (Fall 2018) -  Course website
  4. Optimization Theory, Universidad del Norte, Colombia (Spring 2018) - Course website
  5. Optimization Theory, Universidad del Norte, Colombia (Fall 2017) - Course website
  6. Non-Linear Optimization, Universidad del Norte, Colombia (Fall 2017) - Course website
  7. Data Mining, Universidad del Norte, Colombia (Spring 2017) - Course website
  8. Optimization Theory, Universidad del Norte, Colombia (Fall 2016) - Course website
  9. Data Assimilation, Universidad del Norte, Colombia (Fall 2016) - Course website

Undergrad-Level Courses:

  1. Optimization, Universidad del Norte, Colombia (Fall 2018)
  2. Optimization, Universidad del Norte, Colombia (Spring 2018)
  3. Computational Solutions to Engineering Problems, Universidad del Norte, Colombia (Fall 2017)
  4. Computational Solutions to Engineering Problems, Universidad del Norte, Colombia (Spring 2017)
  5. Computational Solutions to Engineering Problems, Universidad del Norte, Colombia (Fall 2016)
  6. Data Mining, Universidad del Norte, Colombia (Fall 2016)
  7. Computational Solutions to Engineering Problems, Universidad del Norte, Colombia (Spring 2016)
  8. Data Mining, Universidad del Norte, Colombia (Spring 2016)
  9. Numerical Methods, Virginia Tech, USA (Fall 2015)

Employment:

  1. Chair of the Department of Computer Science, Universidad del Norte, Barranquilla 080001, Colombia. Spring 2018 - Current.
  2. Associate Professor, Department of Computer Science, Universidad del Norte, Barranquilla 080001, Colombia. Spring 2018 - Current.
  3. Assistant Professor, Department of Computer Science, Universidad del Norte, Barranquilla 080001, Colombia. Spring 2016 - Fall 2017.
  4. Instructor, Department of Computer Science, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA 24060, USA. Fall 2015.
  5. Summer Student, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. Summer 2014.
  6. Givens Associate, Argonne National Laboratory, Chicago, IL 60290, USA. Summer 2013.
  7. Research Assistant, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA 24060, USA. Fall 2011 - Spring 2015.

Peer-Reviews:

  1. Quarterly Journal of the Royal Meteorological Society, Wiley. Journal website.
  2. International Journal of Computer Mathematics, Taylor & Francis. Journal website.
  3. Applied Numerical Mathematics, Elsevier. Journal webiste.
  4. Journal of Computational and Applied Mathematics, Elsevier. Journal website.
  5. Soft Computing, Springer. Journal website.
  6. International Journal of Artificial Intelligence, CESER. Journal website.

Awards:

  1. Best Workshop Paper Award. A Surrogate Model Based On Mixtures Of Taylor Expansions For Trust Region Based Methods. ICCS 2017, Zurich, Zwitserland, June 2017.

Selected Journal Publications (for a complete list, please check my ORCID http://orcid.org/0000-0001-7784-8163)

  1. Nino-Ruiz, E. D. "Non-linear data assimilation via trust region optimization". Computational and Applied Mathematics, Springer,  38:129 (2019)
  2. Elias D. Nino-Ruiz, Carlos Ardila, Jesus Estrada and Jose Capacho. "A reduced-space line-search method for unconstrained optimization via random descent directions". Applied Mathematics and Computation, Elsevier, 341(2018): 15-30.
  3. Elias D. Nino-Ruiz & Luis E. Morales-Retat. "A Tabu Search implementation for adaptive localization in ensemble-based methods". Soft Computing, Springer (2018)
  4. Nino-Ruiz, Elias D.; Cheng, Haiyan; Beltran, Rolando. "A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models." Atmosphere 9, no. 4: 126. (2018)
  5. Elias D. Nino-Ruiz. "Implicit Surrogate Models For Trust Region Based Methods", Journal of Computational Science, Elsevier, (2018)
  6. Elias D. Nino-Ruiz, Adrian Sandu, and Xinwei Deng. "An Ensemble Kalman Filter Implementation Based on Modified Cholesky Decomposition for Inverse Covariance Matrix Estimation", SIAM Journal on Scientific Computing 40:2, A867-A886 (2018)
  7. Elias D. Nino-Ruiz, and Adrian Sandu. "Efficient Parallel Implementation of DDDAS Inference using an Ensemble Kalman Filter with Shrinkage Covariance Matrix Estimation". Cluster Computing, Springer. (2017)
  8. Vicente Mercado, Elias D. Nino, and Carlos Arteta. "Dynamic Site Response Characterization Via Bayesian Inference: Analysis of the SGC Station Deposit in Bogota, Colombia". Journal of Earthquake Engineering, Taylor & Francis. (2017).
  9. Elias D. Nino-Ruiz, "A Matrix-Free Posterior Ensemble Kalman Filter Implementation Based on a Modified Cholesky Decomposition", Atmosphere Journal, MDPI Publisher, 8:125, (2017).
  10. Vishwas Rao, Adrian Sandu, Michael Ng, and Elias D. Nino-Ruiz. "Robust Data Assimilation Using $L_1$ and Huber Norms", SIAM Journal on Scientific Computing, SIAM, 39:3, B548-B570, (2017).
  11. Elias D. Nino-Ruiz, Adrian Sandu, and Xinwei Deng. "A parallel implementation of the ensemble Kalman filter based on modified Cholesky decomposition", Journal of Computational Science, Elsevier, (2017).
  12. Nino-Ruiz, E.D., Ardila, C. & Capacho, R. "Local search methods for the solution of implicit inverse problems", Soft Computing, Springer (2017). doi:10.1007/s00500-017-2670-z.
  13. Cosmin G. Petraa, Victor M. Zavalab, Elias D. Nino-Ruiz, and Mihai Anitescud. "A high-performance computing framework for analyzing the economic impacts of wind correlation." Electric Power Systems Research, Elsevier, 141 (2016): 372-380.
  14. Ruiz, Elias D. Nino, and Adrian Sandu. "A derivative-free trust region framework for variational data assimilation." Journal of Computational and Applied Mathematics, Elsevier, 293 (2016): 164-179.
  15. Ruiz, Elias D. Nino, Adrian Sandu, and Jeffrey Anderson. "An efficient implementation of the ensemble Kalman filter based on an iterative Sherman–Morrison formula." Statistics and Computing, Springer, 25.3 (2015): 561-577.
  16. Nino-Ruiz, Elias D., and Adrian Sandu. "Ensemble Kalman filter implementations based on shrinkage covariance matrix estimation." Ocean Dynamics, Springer, 65.11 (2015): 1423-1439.

Selected Conference Papers (for a complete list, please check my ORCID http://orcid.org/0000-0001-7784-8163)

  1. 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. 2018
  2. Elias D. Nino-Ruiz, Carlos J. Ardila, Alfonso Mancilla, Jesus Estrada, A Surrogate Model Based On Mixtures Of Taylor Expansions For Trust Region Based Methods, Procedia Computer Science, Volume 108, 2017, Pages 1473-1482, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2017.05.200.
  3. Elias D. Nino-Ruiz, Alfonso Mancilla, Juan C. Calabria, A Posterior Ensemble Kalman Filter Based On A Modified Cholesky Decomposition, Procedia Computer Science, Volume 108, 2017, Pages 2049-2058, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2017.05.062.
  4. Nino-Ruiz, Elias D., Adrian Sandu, and Xinwei Deng. "A parallel ensemble Kalman filter implementation based on modified Cholesky decomposition." Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems. ACM, 2015.
  5. Nino, Elias D., and Adrian Sandu. "Variational Data Assimilation Based on Derivative-Free Optimization." Dynamic Data-Driven Environmental Systems Science. Springer International Publishing, 2015. 239-250.
  6. Nino-Ruiz, Elias D., and Adrian Sandu. "An Efficient Parallel Implementation of the Ensemble Kalman Filter Based on Shrinkage Covariance Matrix Estimation." Proceedings of the 2015 IEEE 22nd International Conference on High Performance Computing Workshops (HiPCW). IEEE Computer Society, 2015.
  7. Nino, Elias D., Carlos J. Ardila, and Anangelica Chinchilla. "A novel, evolutionary, simulated annealing inspired algorithm for the multi-objective optimization of combinatorial problems." Procedia Computer Science 9 (2012): 1992-1998.

Call for Papers (Guest Editor):

  1. Special Issue of Atmosphere Journal in Efficient Formulation and Implementation of Data Assimilation Methods. Special Issue website (CLOSED). 2017.
  2. Special Issue of International Journal of Artificial Intelligence (IJAI) in Combinatorial Optimizaion Methods for Inverse Problems. Special Issue website (CLOSED). 2018.
  3. Special Issue of International Journal of Artificial Intelligence (IJAI) in Combinatorial Optimization.  Special Issue website (CLOSED). 2013

WORD CLOUD of some of my papers:


TALKS

  1. 22/01/2019 - ISDA 2019 - 7th International Symposium on Data Assimilation, RIKEN R-CCS, Kobe, Japan (ENGLISH). (Video)
  2. 27/11/2018 - Seminar of the Ph.D. in Mathematical Engineering, Universidad EAFIT, Colombia (SPANISH). (Video)


ORCID (Link above or just scan the image below):