David R. Penas
PhD in Computer Science
My name is David Rodríguez Penas (Santiago de Compostela, 1987). I received my BASc in Computer Engineering from University of Santiago de Compostela (USC) in 2011, and my MSc in High Performance Scientific Computing from USC in 2012, achieving USC Best Master's thesis Award. In June 2017 I obtain my European PhD at University of Coruña (UDC), developed under the supervision of Professor Julio R Banga, from Marine Research Institute, Spanish National Research Council (IIM-CSIC), and Professors Patricia González and Ramón Doallo, from Computer Architecture Group (GAC-UDC). I obtained the top qualification of "Sobresaliente Cum Laude" and the UDC Best PhD Thesis Award 2016-2017. Currently, I am postdoc researcher from Institute of Mathematics (IMAT-USC), working in a set of projects related with High Performance Computing and Operations Research fields.
During my PhD, I applied high performance computing techniques and Big Data technology to improve heuristics used to address mathematical optimization problems arose in computational Systems Biology. Thus, my PhD was an interdisciplinary work, being a union among Operations Research, Computer Science and Computational Biology. Currently, during my postdoc in IMAT-USC, I am working on another class of Operations Research problems related to logistics and planning. Therefore, my research is focused in (1) developing new hybrid heuristics to solve problems motivated by real-world situations, such as GO problems, MINLP, polynomial programming, or parameter estimation problems, (2) applying different strategies to enhance the resolution in optimization problems such as mathematical decomposition techniques (i.e. Lagrangian Relaxation) or parallel programming, (3) using calibrated penalized methods to solve constrained problems, (4) building cooperative optimization schemes to obtain faster a good solution in complexity problems, and (5) modeling planning route problems. Moreover, I have been worked on a project for transfer of mathematics to the industry during 2018-2019: collaboration between Repsol Company and Technological Institute for Industrial Mathematics (ITMATI) to optimize their industrial process plants.
8. A metaheuristic penalty approach for the starting point in nonlinear programming. D.R. Penas and M. Raydan. RAIRO Operations Research, (under review).
7. Hybrid parallel multimethod hyperheuristic for mixed-integer dynamic optimization problems in computational systems biology. P. González, P. Argüeso-Alejandro, D.R. Penas, X.C. Pardo, J. Saez-Rodriguez, J.R. Banga, and R. Doallo. The Journal of Supercomputing, 75(7), pp 3471-3498, 2019.
6. Enhanced global optimization methods applied to complex fisheries stock assessment models. D.R. Penas, A. Gómez, B.B. Fraguela, M.J. Martín, and S. Cerviño. Applied Soft Computing, 77, pp 50-66, 2019.
5. Multimethod optimization in the cloud: A case-study in systems biology modelling. P. González, D.R. Penas, X.C. Pardo, J.R. Banga, and R. Doallo. Concurrency Computat Pract Exper. 30(12): e4488, 2018.
4. A parallel metaheuristic for large mixed-integer nonlinear dynamic optimization problems, with applications in computational biology. D.R. Penas, D. Henriques, P. González, R. Doallo, J. Saez-Rodriguez, and J.R. Banga. PLOS ONE, 12(8): e0182186, 2017.
3. A cloud-based enhanced differential evolution algorithm for parameter estimation problems in computational systems biology. D. Teijeiro, X. Pardo, D.R. Penas, P. González, J.R. Banga and R. Doallo. Cluster Computing, 20(3), pp 1937-1950, 2017.
2. Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy. D.R. Penas, P. González, J.A. Egea, R. Doallo and J.R. Banga. BMC bioinformatics. 18:52, 2017.
1. Enhanced parallel Differential Evolution algorithm for problems in computational systems biology. D.R. Penas, J.R. Banga, P. González, and R. Doallo. Applied Soft Computing. 33-0, pp. 86 - 99, 2015.
6. Multimethod Optimization for Reverse Engineering of Complex Biological Networks. P. González, D.R. Penas, X. Pardo, J.R. Banga and R. Doallo. Proceedings of the 6th International Workshop on Parallelism in Bioinformatics. pp. 11 - 18. ACM Digital Library, 2018.
5. Using the Cloud for Parameter Estimation Problems: Comparing Spark vs MPI with a Case-Study. P. González, X. Pardo, D.R. Penas, D. Teijeiro, J.R. Banga and R. Doallo. Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. pp. 797 - 806. ACM Digital Library, 2017.
4. Evaluation of parallel Differential Evolution implementation on MapReduce and Spark. D. Teijeiro, X. C. Pardo, D.R. Penas, P. González, J.R. Banga and R. Doallo. Euro-Par 2016: Parallel Processing Workshops. Lecture Notes in Computer science. 10104, pp. 397 - 408. Springer, 2016.
3. Parallel Metaheuristics in Computational Biology: An Asynchronous Cooperative Enhanced Scatter Search Method. D.R. Penas, P. González, J.A. Egea, J.R. Banga, and R. Doallo. Procedia Computer Science. 51, pp. 630 - 639. Elsevier, 2015.
2. A Parallel Differential Evolution Algorithm for Parameter Estimation in Dynamic Models of Biological Systems. D.R. Penas, J.R. Banga, P. González, and R. Doallo. Advances in Intelligent Systems and Computing. 294, pp. 173 - 181. Springer, 2014.
1. A Study of Semantic Proximity between Archetype Terms Based on SNOMED CT Relationships. J.L. Allones, D.R. Penas, M. Taboada, D. Martínez, and S. Tellado. Lecture Notes in Computer Science, 7738, pp. 98 - 112. Springer Berlin Heidelberg, 2013.
- XXXVIII Congreso Nacional de Estadística e Investigación Operativa (SEIO). Alcoy, Spain, 2019.
- XIII Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB-CAEPIA). 2018.
- XXXVII Congreso Nacional de Estadística e Investigación Operativa (SEIO). Oviedo, Spain, 2018.
- XIII Congreso Galego de Estatística e Investigación de Operacións (SGAPEIO). Ferrol, Spain, 2017.
- International Conference on Systems Biology (ICSB). Barcelona, Spain, 2016.
- Bioinformatics for Young international researchers Expo: Maastricht-Aachen-Liege (ByteMAL). Aachen, Germany, 2016.
- Advanced Lecture Course on Computational Systems Biology (ACSB). Aussois, France, 2015.
- 8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB). Salamanca, Spain, 2014.
- Mathematical optimization
- Distributed computing
- High performance computing
- Big data
- Machine learning
- Intelligence Artificial
- David R. Penas and Natalia Costas Lago. Deployment of HPC services in multipurpose cloud environments. CESGA technical report / Master’s Thesis, 2012. https://www.cesga.es/es/biblioteca/downloadAsset/id/706
- David R. Penas and Natalia Costas Lago. Networking virtualization technologies analysis and their application to NREN networks. CESGA technical report, 2011. https://www.cesga.es/es/biblioteca/downloadAsset/id/705
- The Role of Mathematical Programming in Data Science, University of Santiago de Compostela, November 19th -23th 2018.
- Decomposition Techniques in Mathematical Programming, University of Santiago de Compostela, June 4th - 7th 2018.
- Advanced Lecture Course on Computational Systems Biology. Aussois, France, April 6th- 11th 2015.
- Introduction course of Hadoop, January 2015, University of A Coruna.
- Introduction course of mathematical optimization, University of Santiago de Compostela, June 2013.
- SOA/WOA course, CESGA foundation, Santiago de Compostela, May 2010.
- You can download my CV here: