Dr. Abdel Rodriguez joins esqLABS

 

From May 23, 2020 on Dr. Abdel Rodriguez, a trained Software and Machine Learning Engineer from University of Las Villas, Cuba, and Brussels, Belgium, will be reinforcing esqLABS.

 

WE WELCOME ABDEL TO THE TEAM!

Dr. Abdel Rodriguez joins esqLABS

Dr. Abdel Rodríguez is a Computer Scientist with academic and industrial experience. He has balanced theory and practice experience in the field of Computer Science. He holds a MSc in Bioinformatics, a PhD in Machine Learning and more than ten years of experience as a software developer.

After finishing his bachelor’s degree in Computer Science, Abdel completed a MSc focused on Bioinformatics using supervised learning to detect virus drug resistance. He immediately started working as a Teaching Assistant at Central University of Las Villas, Cuba and started a PhD at Vrije Universiteit Brussels, Belgium. His PhD focused on Reinforcement Learning and Intelligent Control. He succeeded in controlling different industrial setups under collaboration with the Flanders’ Mechatronics Technology Centre on the international project LeCoPro (grant no. 80032). Back to Cuba he scaled up to Adjugated Professor and give lectures on general Artificial Intelligence and Advanced Programming topics. He enrolled as a software developer in several projects as a freelancer.

Before joining esqLABS, Abdel had put together experience on several theoretical aspects on Computer Science and practices on software development. He worked as a Software Engineer and Artificial Intelligence consultant at Addiva AB, Sweden and as a Software Engineer at Insiders Technologies GmbH, Germany.

Most relevant scientific publications:

Journal publications

  1. A. Rodríguez, P. Vrancx, R. Grau, A. Nowé: A reinforcement learning approach to coordinate exploration with limited communication in continuous action games. Knowledge Eng. Review 31(1): 77-95 (2016)
  2. P. Vrancx, P. Gurzi, A. Rodríguez, K. Steenhaut, A. Nowé: A Reinforcement Learning Approach for Interdomain Routing with Link Prices. TAAS 10(1): 5:1-5:26 (2015)
  3. A. Rodríguez, I. Bonet, R. Grau, M.M. García: Judges System for Classifiers Specialization. International Journal of Biological, Biomedical and Medical Sciences 3(2) (2008)

International congresses and book chapters

  1. E. Ramentol, J. Madera and A. Rodríguez. The diagnosis of undergraduate drop out in Informatics Engineering using a new model based on probabilistic rough set theory. Springer volume “Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications” (In press) 2018.
  2. E. Ramentol, J. Madera, A. Rodríguez and R. Bello. The diagnosis of undergraduate drop out in Informatics Engineering using a new model based on probabilistic rough set theory. International Symposium on Fuzzy and Rough Sets (ISFUROS 2017).
  3. I. Bonet, A. Rodríguez, I. Grau: Bidirectional Recurrent Neural Networks for Biological Sequences Prediction. MICAI (2) 2013: 139-149
  4. A. Rodríguez, P. Vrancx, A. Nowé, and E. Hostens. Model-free learning of wire winding control. In Proceedings of the Asian Control Conference (ASCC-2013), IEEE.
  5. A. Rodríguez, P. Vrancx, R. Grau-Ábalo, A. Nowé: An RL approach to common-interest continuous action games. AAMAS 2012: 1401-1402
  6. K. Van-Vaerenbergh, A. Rodríguez, M. Gagliolo, P. Vrancx, A. Nowé, J. Stoev, S. Goossens, G. Pinte, W. Symens: Improving wet clutch engagement with reinforcement learning. IJCNN 2012: 1-8
  7. A. Rodríguez, P. Vrancx, R. Grau, and A. Nowé. An RL Approach to Coordinate Exploration with Limited Communication in Continuous Action Games. In ALA-2012, 2012
  8. A. Rodríguez, R. Grau -Ábalo, A. Nowé: Continuous Action Reinforcement Learning Automata – Performance and Convergence. ICAART (2) 2011: 473-478
  9. I. Bonet, A. Rodríguez, R. Grau-Ábalo, M.M. García: Ensemble of Classifiers Based on Hard Instances. MCPR 2011: 67-74
  10. A. Rodríguez, M. Gagliolo, P. Vrancx, R. Grau, and A. Nowé. Improving the performance of Continuous Action Reinforcement Learning Automata. In 9th European Workshop on Reinforcement Learning, EWRL 2011, 2011
  11. M. Gagliolo, K. Van- Vaerenbergh, A. Rodríguez, A. Nowé, S. Goossens, G. Pinte, and W. Symens. Policy gradient methods for controlling systems with discrete sensor information. In 20th Annual Belgian-Dutch Conference on Machine Learning — BeNeLearn, pages 115–116, 2011
  12. M. Gagliolo, K. Van-Vaerenbergh, A. Rodríguez, A. Nowé, S. Goossens, G. Pinte, and W. Symens. Policy search reinforcement learning for automatic wet clutch engagement. In 15th International Conference on System Theory, Control and Computing — ICSTCC 2011, pages 250–255. IEEE, 2011
  13. S. Goossens, G. Pinte, W. Symens, M. Gagliolo, A. Rodríguez, and A. Nowé. Reinforcement learning for repetitive systems with discrete sensors. In 30th Benelux Meeting on Systems and Control — Book of Abstracts, page 149. Universiteit Gent, 2011
  14. I. Bonet, A. Rodríguez, R. Grau-Ábalo, M.M. García, Y. Saeys, A. Nowé: Comparing Distance Measures with Visual Methods. MICAI 2008: 90-99

Get in touch now

Contact

Contact

ESQlabs GmbH | Am Sportplatz 7 | 26683 Saterland | Germany
Tel. +49 151 / 58559070 | info@esqLABS.com

This site does not use cookies to track your personal information

Menu

 

Links