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Current Position

Researcher assistant professor at Enginyeria i Arquitectura La Salle, Universitat Ramon Llull

Education

1. PhD in Computer Engineering: 2004 — 2008
   PhD under the program: Communication and Information Systems and its Management.
   Enginyeria i Arquitectura La Salle, Universitat Ramon Llull.
   Dissertation Title: “New Challenges in  Learning Classifier Systems: Mining Rarities and Evolving Fuzzy Models”
   Thesis Supervisor: Ester Bernadó-Mansilla
   Examining Committee: David E. Goldberg, Francisco Herrera, Martin V. Butz, Xavier Llorà, and Xavier Vilasís.
2. DEA in Computer Engineering: 2004 — 2006.
   Enginyeria i Arquitectura La Salle, Universitat Ramon Llull.
   Dissertation Title: “Facetwise Analysis of Learning Classifier Systems for Mining Rarities”
   DEA Supervisor: Ester Bernadó-Mansilla
3. MS  in Computer Engineering: 2002 — 2004.
   Enginyeria i Arquitectura La Salle, Universitat Ramon Llull.
   Thesis Title: “Development and Integration of the XCS Classifier System in KEEL and analysis of rule set reduction mechanisms” (A with Honors)
   Thesis Supervisor: Ester Bernadó-Mansilla
   Best student of the promotion
4. MSc in Computer Engineering: 1999 — 2002.
   Enginyeria i Arquitectura La Salle, Universitat Ramon Llull.
   Thesis Title: “Comparative Platform among Genetic Algorithms, Evolution Strategies, and Simulated Annealing” (A with Honors)
   Thesis Supervisor: Josep M. Garrell Guiu
   Best student of the promotion

Research Experience

1. Member of the Research Group in Intelligent Systems (GRSI): 2001 — present.
   GRSI is a research group which has been recognized by the Catalan government, the Generalitat de Catalunya, under the reference 2005SGR-00302. The group focuses its research on practical applications of evolutionary computation    and soft-case-based reasoning.Among others, the research group participates in the following projects:
   1. Artificial Intelligence Telematic Network: 2003  –  present. The aim of this project is to coordinate and try to enhance the collaboration among research groups in the field of artificial intelligence. This project is funded by the Spanish government under grant 2003XT00075.
   2. Spanish Network on Data Mining and Machine Learning: 2003  –  2004. This project is funded by the Spanish government under grant TIC2002-11124-E.
2. Member of the Illinois Genetic Algorithm Laboratory (IlliGAL): 2006-present.
   The IlliGAL, placed in the General Engineering Department (University of Illinois at Urbana    champaign), is one of the most important research groups in genetic algorithms and    genetic-based machine learning. At the IlliGAL, researches study nature’s search algorithm of choice,    genetics, and evolution, as a practical approach to solving difficult problems on a computer. Theory and empirical results obtained in the lab demonstrate that well-designed genetic algorithms can be guaranteed to solve a broad class of provably hard problems quickly, reliably, and accurately. The quality of the research of the group is highlighted by the large number of publications of    the director of the lab, Professor David E. Goldberg—one of the top 20 most cited  authors in computer science more generally according to Palsberg—who has published more than 400 scientific publications in international journals, referred conferences, and book chapters.

Participation in Research Projects

1. KEEL III: Genetic-based machine learning, data complexity, unbalanced domains, data streams, and scalability: 2009 – present.
   KEEL III is a continuation of KEEL II, which aims at conducting research on some of the hot topics in data mining such as evaluate the complexity of classification domains, learn from unbalanced domains and data streams, and improve the scalability of existing algorithms—and build new scalable methods—in order to solve large problems. The project is sponsored by the Ministerio de Educación y Ciencia under the national project with reference TIN2008-06681-C06-05.
2. KEEL II: Rule-based Evolutive Models: 2005 — 2008.
   KEEL II continues with the development of a machine learning tool initiated in the KEEL project. In KEEL II, we are introducing the following novelties to the prototype: (1) new machine learning techniques and (2) algorithm evaluation methodologies.The project is sponsored by the Ministerio de Educación y Ciencia under    the national project with reference TIN2005-08386-C05-04.
3. KEEL: Knowledge Extraction with Evolutionary Learning: 2002 — 2005.
   The KEEL project develops a software tool that integrates a large variety of genetic-based machine learning techniques for pattern classification,    regression, and clustering; it includes the top-notch evolutionary learning methodologies. KEEL provides an intuitive visual tool that permits to run experiments, compare algorithms, and extract classification models for user’s classification, regression, and unsupervised problems.The following five universities participate in the project:    Universidad de Granada (UGR), Universidad de Córdoba (UCO), Universitat Ramon Llull (URL), Universidad de Jaén (UJ), and Universidad de Oviedo (UO).The project was sponsored by the Ministerio de Ciencia y Tecnología under the national project with reference TIC2002-04036-C05-03.

Teaching Experience

1. Teaching Artificial Intelligence: 2008 — present. Subject of the 5th course of    Computer  Engineering, Enginyeria i Arquitectura La Salle,    Universitat Ramon Llull. I give the classes in English.
2. Advanced Programming: 2008 — present. Subject of the 2nd course of Computer  Engineering, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull.
3. Teaching Data structures: 2003 — 2008. Subject of the 2nd course of Computer Engineering, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull. Since 2007, I give the classes in English.
4. Supervisor of Master Thesis: 2003 — present. Supervisor of several master thesis of Computer Engineering students.
5. Seminars of optimization and learning with genetic algorithms: 2004 — 2006. Given several seminars in the subject Artificial Intelligence, 5th course of Computer Engineering, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull. These seminars introduce the students to genetic algorithms    in the context of search, optimization, and machine learning.
6. Coordination of seminars of first-year students in the GRSI lab: 2005 — 2006. Coordination of the seminars given to the first-year students in the Research Group of Intelligent Systems lab (GRSI). In these seminars, the students are introduced to several topics in the optimization and machine learning realms.

Visits to Research Groups

1. Illinois Genetic Algorithm Laboratory (IlliGAL): Jun. 2008 — Jul. 2008.
   In this visit, we continued on the investigation of the effect of class imbalances on learning classifier systems, as well as on how we can learn the sub-structure of non-trivial, hierarchical imbalanced problems.
2. Soft Computing and Intelligent Information Systems (SCI2s): Jan. 28 — Mar. 14, 2008.
   In this visit, we continued with the collaboration with several SCI2s members to further improve genetic-based machine learners for evolving linguistic fuzzy rules. Moreover, in this visit we also collaborated in the emerging field of data complexity assessment for supervised learning.
3. Soft Computing and Intelligent Information Systems (SCI2s): Mar. 11 — Mar. 25, 2007.
   In this visit, I collaborated with Jorge Casillas and other members of the SCI2s group to develop different genetic-based machine learning systems. We designed a new online supervised learning process based on a Michigan-style learning fuzzy-classifier system. The algorithm, called Fuzzy-UCS, is inspired by UCS, an existing learning classifier system for classification tasks. Fuzzy-UCS introduces a linguistic fuzzy representation to the rules with the aim of evolving more readable rule sets and providing a reasoning methodology more similar to human one, while maintaining similar performance and generalization capabilities than those presented by UCS.
4. Illinois Genetic Algorithm Laboratory (IlliGAL): Jul. 2006 — Dec. 2006.
   In this visit, we developed facetwise models of learning classifier systems for learning from environments with rare cases or classes. The research resulted in the publication of several scientific papers.

Awards & Grants

1. Best student paper award in the 2008 ESTYLF conference for the paper Albert Orriols-Puig, Jorge Casillas, and Francisco J. Martínez-López. Modelado Causal en Marketing Mediante Aprendizaje no Supervisado de Reglas de Asociación Difusas. XIV Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF’08).
2. Best paper award in the Genetic and Evolving Fuzzy Systems Workshop in 2008 for the paper Jorge Casillas, Albert Orriols-Puig, and Ester Bernadó-Mansilla. Toward Evolving Consistent, Compete, and Compact Fuzzy Rule Sets for Classification Problems. In Genetic and Evolving Fuzzy Systems, pages 89-94, IEEE, 2008.
3. Beca BE (2008). Scholarship to visit foreign research groups. This scholarship is granted by the Generalitat de Catalunya. The scholarship is funding my research visit to the IlliGAL, scheduled for the next June and July, 2008. Ref: 2007BE-200124.
4. GECCO’08 travel grant. Grant given to the students that have, at least, one paper in the 2008 Genetic and Evolutionary Conference.
5. GECCO’07 travel grant. Grant given to the students that have, at least, one paper in the 2007 Genetic and Evolutionary Conference.
6. Best paper nomination in the Genetic and Evolutionary Computation Conference in 2006 for the paper Albert Orriols-Puig and Ester Bernadó-Mansilla. Bounding XCS Parameters for Unbalanced Datasets. Proceedings of the 2006 Genetic and Evolutionary Computation Conference. Seattle, WA. 2006.
7. GECCO’06 travel grant. Grant given to the students that have, at least, one paper in the 2006 Genetic and Evolutionary Conference.
8. Beca BE (2006). Scholarship to visit foreign research groups. This scholarship is granted by the Generalitat de Catalunya. The scholarship funded my research visit to the Illinois Genetic Algorithms Laboratory (IlliGAL) done from July 16, 2006 to December 16, 2006. Ref: 2006BE-00299.
9. Grant fundación Rafael Escolà la Excelencia Universitaria (2005). Grant given to the three best engineers of the year (including the disciplines of general engineering, telecomunications engineering, and computer science engineering).
10. Beca FI (2004 — present). Scholarship for researchers formation. Ref: 2005FI-00252.
11. Becas Líder de Inmersión a la Realidad Social Española (July 2004). Fellowship granted to the 8 best Spanish students. Sponsors: Grupo Santander, Hoteles NH and Fundación Carolina.
12. Beca Colaboración (2003). Scholarship to fund the collaboration of a last-year student with a research project of a research group of the University. Ministerio de Ciencia, Cultura y Deporte.
13. Beca Universitaria de la Caixa de Manresa (2000). Scholarship given to the best students of the year in Catalonia.
14. Beca Universitaria de la Caixa de Manresa (1999). Scholarship given to the best students of the year in Catalonia.

Professional Activities

1. Co-organizer of the special session “Knowledge Extraction based on Evolutionary Learning” in the 4th International Conference on Hybrid Artificial Intelligent Systems, 2009.
2. Reviewer, IEEE Transactions on Evolutionary Computation
3. Reviewer, Pattern Recognition Letters
4. Reviewer, International Journal of Hybrid Intelligent Systems
5. Reviewer, Genetic and Evolutionary Computation Conference
6. Reviewer, International Workshop on Learning Classifier Systems
7. Reviewer, Bio-Inspired Computing: Theory and Applications
8. Reviewer, World Multi-Conference on Systemics, Cybernetics and Informatics
9. Reviewer, Hybrid Intelligent Systems Conference

Invited Talks

1. Learning Classifier Systems: New Trends, in I Workshop on Knowledge Extraction based on Evolutionary Learning, May 2008.
2. Some results on the use of UCS for imbalanced data sets, in I Workshop on Knowledge Extraction based on Evolutionary Learning, May 2008.
3. Can LCSs learn from Rare Classes? Univesity of Granada, March 2007.

Coauthors

1. David E. Goldberg  (University of Illinois, USA, h-index = 59)
2. Tin Kam Ho (Bell Labs, USA, h-index = 18)
3. Pier Luca Lanzi (Politecnico di Milano, Italy, h-index = 18)
4. Kumara Sastry (University of Illinois, USA, h-index = 16 )
5. Jorge Casillas (Universidad de Granada, Spain, h-index = 15)
6. Ester Bernadó-Mansilla (Universitat Ramon Llull, Spain, h-index=7)
7. Francisco J. Martínez-López (University of Granada, Spain)
8. Núria Macià (Universitat Ramon Llull, Spain)
9. Joaquim Rios-Boutin (Universitat Ramon Llull, Spain)
10. Francesc Teixidó-Navarro (Universitat Ramon Llull, Spain)
11. Sergio Morales-Ortigosa (Universitat Ramon Llull, Spain)

Source Code

1. Extended Compact Genetic Algorithm in Matlab. Kumara Sastry, Albert Orriols-Puig.
   Documentation: http://www.illigal.uiuc.edu/pub/papers/IlliGALs/2007009.pdf
   Source: http://www.illigal.uiuc.edu/pub/src/ECGA/eCGAmatlab.zip
2. Complexity Metrics Library in C++. Albert Orriols-Puig
   Documentation: (temporarily not available)
   Source: (temporarily not available)
3. The eXtended Classifier System (XCS). Albert Orriols-Puig.
   Documentation: http://www.keel.es
   Source: http://www.keel.es
4. The sUpervised Classifier System (UCS). Albert Orriols-Puig
   Documentation: http://www.keel.es
   Source: http://www.keel.es