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Sebastián Ventura
http://www.uco.es /users/sventura
Short Curriculum Vitae
I. Profesional data
Affiliation:
Official address:
Department of Computer Science and Numerical Analysis. University of Córdoba.
Campus Universitario de Rabanales, edificio “Albert Einstein”, 3ª planta
14071 – Córdoba (Spain)
Current position(s)
Associate Professor (accredited to Full Professor)
Phone: +34 957212218
Fax: +34 957218630
e-mail: [email protected]
Personal URL : http://www.uco.es/users/sventura
II. Education
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B.S. Degree in Chemistry 1989 (University of Córdoba)
PhD Degree in Sciences 1996 (University of Córdoba)
Dissertation title: Design of Artificial Neural Networks in Kinetic Methods.
III. Teaching Experience
Since 1998 is Associate Professor on Computer Science and Artificial Intelligence in the University of
Córdoba. He got the accreditation to Full Professor for Spanish Universities in May 2012.
1996-1998 – Assistant Professor. Department of Computer Science and Numerical Analysis. University of
Córdoba
1991-1998 – Secondary Education Teacher.
IV. Experience in other scientific, academic and management positions
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Head of the Department of Computer Science and Numerical Analysis (University of Cordoba).
December 2002 – December 2007.
Affiliated Professor. Department of Computer Science. Virginia Commonwealth University
(Richmond, Virginia, USA). Since August 2008
Distinguished Adjunct Professor. King Abdulaziz University (Jeddah, Saudi Arabia). Since April
2013.
Chief Information Officer. University of Cordoba. November 2013 – June 2014.
Chair of Doctoral Program “Advanced Computing, Energy and Plasmas”. University of Cordoba.
V. Research experience
Professor Ventura has been director or responsible of research in the following national (Spanish) projects:
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Data Mining with More Flexible Representations. Project TIN2014-55252-P (Ministerio de Economía
y Competitividad). From 2015/1/1 to 2017/12/31.
New Problems in Knowledge Discovery: A Genetic Programming Approach. Project TIN2011-22408
(Ministerio de Educación y Ciencia). From 2012/1/1 to 2014/12/31.
Actual tendencies and New Challenges in KEEL: Multi-Instance Learning, Evolutionary Neural
Networks, Educational Data Mining and Web Data Mining. Project TIN2008-06681-C06-03/TIN
(Ministerio de Educación y Ciencia). From 2009/1/1 to 2011/12/31.
Aplicación de Técnicas de Extracción de Conocimiento a la Mejora de los Sistemas Educativos
(ATECSE). Proyecto de Excelencia (Junta de Andalucía). From 2009/1/14 to 2012/1/13.
Also, he has participated as researcher in about 10 national projects in the last years.
VI. Other scientific activities
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International conference on educational data mining (EDM)
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Congreso Español de Algoritmos Evolutivos y Bioinspirados (MAEB)
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2009-2015 – Member of the Program Committee
World Congress on Nature and Biologically Inspired Computing (NaBIC).
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2008-2010 – Member of Program Committee
2011 – General Co-Chair
2012 – General Co-Chair
Genetic and Evolutionary Computation Conference (GECCO)
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2008-2015 – Member of the Program Committee
International Conference on Intelligent Systems Design and Applications (ISDA)
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2008 – Member of the Program Committee
2010 – Member of the Program Committee
International Conference on Hybrid Intelligent Systems
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2006-2011 – Member of Program Committee.
IEEE World Congress on Computational Intelligence (WCCI)
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2002, 2003 – Member of Program Committee
2004 – Member of Program and Local Committees
2005-2014 – Member of Program Committee
WWW/Internet
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2008 – Member of Program Committee
2009 – General chair
2010 – Member of Program Committee
2011 – Program chair
2012-2014 – Member of Program Committee
2015 – Doctoral Consortium Chair
2009-2014 – Member of Program Committee.
2015 – Member of the International Advisory Board
International Conference on Soft Computing and Pattern Recognition (SOCPAR)
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Conference of the Spanish Association of Artificial Intelligence
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2011- Member of Program Committee.
IEEE System, Man and Cybernetics Conference
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2009-2011 – Member of Program Committee.
2014 – Member of the International Advisory Board
2015 – Member of the International Advisory Board
2013-2015 – Member of Program Committee
SOCO conference
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2013-2015 – Member of Program Committee
VII. Editorship activity
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Co-editor of the book “Actas del III Congreso de Algoritmos Evolutivos y Bioinspirados, MAEB’04”.
Co-editor of the book “Data Mining and e-learning”, WIT Press, 2006.
Co-editor of the book “Handbook on Educational Data Mining”. Taylor Francis / CRC, 2010.
Co-editor of the book “Proceedings of the Eleventh International Conference on Intelligent Systems,
Design and Applications”. IEEE Press, 2011.
Co-editor of the book “Proceedings of the Twelve International Conference on Intelligent Systems,
Design and Applications”. IEEE Press, 2011.
Editor of the book “Genetic Programming: New Approaches and Successful Applications”, InTech
Publishing, 2012.
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Coeditor of the book “Trends in Practical Applications of Agents and Multi-Agents Systems, 12
International Conference”, Springer, 2014.
Co-editor of the special issue “Data mining for personalised educational systems”. User Modelling
and User Adapted Interaction, 2011.
Co-editor of the special issue “Intelligent Data Analysis”. Journal of Computer and System Sciences,
2013.
Co-editor of the special issue “Advances in learning schemes for function approximation”,
Neurocomputing, 2014.
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Editorial board member of the “Journal of Educational Data Mining” since 2008.
Editorial board member of the “Applied Computational Intelligence and Soft Computing” journal
since 2011.
Editorial board member of the “PeerJ Computer Science” journal since 2015.
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Referee of the “Soft Computing” journal since 2006.
Referee of the “User Modelling and User Adapted Interaction” journal since 2006.
Referee of the “Data Knowledge Engineering” journal since 2008.
Referee of the “Knowledge Based Systems” journal since 2008.
Referee of the “Information Sciences” journal since 2009.
Referee of the “Knowledge and Information Systems” journal since 2009.
Referee of the “Swarm and Evolutionary Computation” journal since 2010.
Referee of the “Neurocomputing” journal since 2012.
Referee of the “IEEE Transactions on Cybernetics” journal since 2012.
Referee of the “IEEE Transactions on Knowledge and Data Engineering” journal since 2012.
Referee of the “Integrated Computer Aided Engineering” journal since 2012.
Referee of the “IEEE Transactions on Neural Networks and Learning Systems” journal since 2014.
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VIII. Plenary Conferences and Talks
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7/2/2008
9/25/2009
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2/26/2010
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3/12/2012
12/10/2013
2/5/2014
9/21/2014
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11/13/2014
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11/20/2014
Data Mining in e-Learning. Universitat Ouverta de Catalunya.
New Trends in Evolutionary Learning. I Jornadas Andaluzas de Informática. Canillas
de Aceituno (Málaga).
Machine Learning Techniques in Automated Document Classification. Aplicación de
Técnicas de Inteligencia Artificial a la documentación histórica. Centro de Estudios
Iberoamericanos. Sevilla.
Introduction to Multiple Instance Learning. University of Granada
Educational Data Mining: Current Research Questions. University of Grenoble
Data Mining in E-Learning. University King Abdulaziz, Jeddah (Saudi Arabia).
¿Puede el aprendizaje automático mejorar el aprendizaje humano? Interacción
2014. Santa Cruz de Tenerife (Spain).
Mejorando el proceso de aprendizaje a través de la minería de datos. EDUTEC
conference. Cordoba (Spain)
Big Data Mining in Health Informatics. Workshop on IT for Clinical Surveillance. King
Abdulaziz University, Jeddah (Saudi Arabia).
IX. Publications
- Is advisor of seven PhD dissertations:
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Cristóbal Romero-Morales. “Applying Knowledge Discovery Techniques to Improve Web-Based
Adaptive Hypermedia Courses”. University of Granada, 2005.
Amelia Zafra-Gómez. “Grammar-guided genetic programming models for multiple instance
learning”. University of Granada, 2009.
Juan Luis Olmo-Ortiz. “Data mining using Ant Programming” University of Córdoba, 2013.
José Luis Ávila-Jiménez. “Genetic Programming Models for Multi-label Classification”. University
of Córdoba, 2013.
José María Luna-Ariza. “New Challenges in Association Rule Mining: an Approach Based on
Genetic Programming”. University of Granada, 2014.
Alberto Cano-Rojas. “New classification models through evolutionary algorithms”. University of
Granada, 2014.
Carlos Marquez-Vera. “Predicting Student Dropout by Data Mining Techniques”. University of
Cordoba, 2015.
- By the present time he has published
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85 scientific papers in refereed journals.
120 papers in books (proceedings of conferences and edited books)
List of most recent journal publications is Appendix 1.
X. Awards and International rankings
H index: 15 (source: Thomson Web of Science)
19 (source: Elsevier SCOPUS)
28 (source: Google Scholar)
- Most cited paper 2006-2007 in the Expert Systems with Applications journal.
- Profesor Antonio Hidalgo award to the paper, “Uso de redes neuronales en la estimación de parámetros
analíticos cinéticos” (best conference paper). Séptimas jornadas de análisis instrumental, Madrid, 1995.
- IEEE Senior Member since 2007.
- ACM Senior Member since 2013.
XI. Areas of interest
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Data, Web and Text Mining
Machine Learning
Soft Computing, Evolutionary Computing, Genetic Programming
Application of Data Mining to Educational Data
Application of Data Mining to Health Data
APPENDIX
List of the most relevant publications (five last years)
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[14]
J. M. Luna, M. Pecheniskiy & S. Ventura. Mining Exceptional Relationships with GrammarGuided Genetic Programming. Knowledge and Information Systems, accepted.
A. Ramírez, J.R. Romero & S. Ventura. An approach for the evolutionary discovery of
software architectures. Information Sciences, 305, 234-256, 2015.
J. M. Luna, C. Romero, J. R. Romero & S. Ventura. An Evolutionary Algorithm for the
Discovery of Rare Class Association Rules in Learning Management Systems. Applied
Intelligence, 42(3), 501-513, 2015.
A. Cano, A. Zafra & S. Ventura. Speeding up Multiple Instance Learning Classification Rules
on GPUs. Knowledge and Information Systems, 44(1), 127-145, 2015.
O. G. Reyes, C. Morell & S. Ventura. Scalable extensions of the ReliefF algorithm for
weighting and selecting features on the multi-label learning context. Neurocomputing, 161,
168-182, 2015.
A. Cano, J. M. Luna, A. Zafra y S. Ventura - A classification module for Genetic
Programming Algorithms in JCLEC. Journal of Machine Learning Research, 16, 491-494,
2015.
E. Gibaja & S. Ventura. A Tutorial on Multi-Label Learning. ACM Computing Surveys, 47(3),
1-38, 2015.
A. Cano, D. T. Nguyen, S. Ventura & K. Cios. ur-CAIM: Improved CAIM Discretization for
Unbalanced and Balanced Data. Soft Computing, 2014.
A. Cano, A. Zafra & S. Ventura. Parallel evaluation of Pittsburgh rule-based classifiers on
GPUs. Neurocomputing, 126, 45-57, 2014.
J. M. Luna, J. R. Romero & S. Ventura. On the Adaptability of G3PARM to the Extraction of
Rare Association Rules. Knowledge and Information Systems, 38(2), 391-418, 2014.
B. Strack, J. P. DeShazo, C. Gennings, J. L. Olmo, S. Ventura, K. J. Cios and J. N. Clore.
Impact of HbA1c measurement on hospital readmission rates: An analysis of 70,000 clinical
database patient records. BioMed Research International, Vol. 2014, ID#781670.
J. M. Luna, J. R. Romero, C. Romero and S. Ventura. On the Use of Genetic Programming
for Mining Comprehensible Rules in Subgroup Discovery. IEEE Trans. on Cybernetics,
44(12), 2329-2341. 2014.
J. M. Luna, J. R. Romero, C. Romero and S. Ventura. Mining optimised quantitative
association rules using a genetic programming free-parameter algorithm. Integrated
Computer-Aided Engineering, 21(4), 321-337, 2014.
O. Reyes, C. Morell & S. Ventura. Learning similarity metric to improve the performance of
the multi-label lazy ranking algorithms. Integrated Computer-Aided Engineering, 21(4), 339354, 2014.
[15] A. Cano, S. Ventura & K. Cios. Scalable CAIM Discretization on Multiple GPUs Using
Concurrent Kernels. J. Supercomputing, 69(1), 273-292, 2014.
[16] J. L. Olmo, J. R. Romero & S. Ventura. Single and multi-objective ant programming for
mining interesting rare association rules. International Journal of Hybrid Intelligent Systems,
11(3), 197-209, 2014.
[17] E. Gibaja & S. Ventura. Multilabel Learning: A Review of the State of The Art and Ongoing
Research. WIRES DMKD, 4(6), 411-444, 2014.
[18] J.L. Olmo, J.R. Romero & S. Ventura. Swarm-based metaheuristics in automatic
programming: a survey. WIRES DMKD, 4(6), 445-469, 2014.
[19] J. M. Luna, J. R. Romero, C. Romero and S. Ventura. On the Use of Genetic Programming
for Mining Comprehensible Rules in Subgroup Discovery. IEEE Transactions on
Cybernetics, 2014 (accepted).
[20] A. Cano, S. Ventura & K. Cios. Scalable CAIM Discretization on Multiple GPUs Using
Concurrent Kernels. J. Supercomputing, 2014 (accepted).
[21] B. Strack, J. P. DeShazo, C. Gennings, J. L. Olmo, S. Ventura, K. J. Cios and J. N. Clore.
Impact of HbA1c measurement on hospital readmission rates: An analysis of 70,000 clinical
database patient records. BioMed Research International, 2014 (accepted).
[22] A. Zafra, C. Romero & S. Ventura. DRAL: A Tool for Discovering Relevant e-Activities for
Learners. Knowledge and Information Systems, 36(1), 211-250, 2013. DOI: 10.1007/s10115012-0531-8.
[23] A. Cano, A. Zafra & S. Ventura. ICRM: An Interpretable Classification Rule Mining Algorithm.
Information Sciences, 240, 1-20, 2013.
[24] A. Cano, A. Zafra & S. Ventura. Weighted Data Gravitation Classification for Standard and
Imbalanced Data. IEEE T on Cybernetics, 43(6), 1672-1687, 2013.
[25] A. Cano, J. M. Luna & S. Ventura. High Performance Evaluation of Evolutionary-Mined
Association Rules on GPUs. Journal of Supercomputing, 66(3), 1438-1461, 2013.
[26] C. Romero, M.-I. Lopez; J. M. Luna & S. Ventura. Predicting students' final performance from
participation in on-line discussion forums. Computers & Education, 68, 453-472.
[27] J. L. Olmo, J.M. Luna, J.R. Romero & S. Ventura. Application of Grammar Guided Ant
Programming Models to Association Rule Mining. Integrated Computed-Aided Engineering,
20(3): 217-234, 2013.
[28] C. Romero, S. Ventura: Data mining in education. Wiley Interdisc. Rew.: Data Mining and
Knowledge Discovery 3(1): 12-27 (2013).
[29] A. Cano, A. Zafra & S. Ventura. Parallel evaluation of Pittsburgh rule-based classifiers on
GPUs. Neurocomputing, 2013 (accepted).
[30] J. M. Luna, J. R. Romero & S. Ventura. On the Adaptability of G3PARM to the Extraction of
Rare Association Rules. Knowledge and Information Systems, 2012 (on line). DOI:
10.1007/s10115-012-0591-9
[31] A. Cano, J. M. Luna & S. Ventura. High Performance Evaluation of Evolutionary-Mined
Association Rules on GPUs. Journal of Supercomputing, 2013 (on line). DOI:
10.1007/s11227-013-0937-4
[32] A. Zafra, M. Pechenizkiy & S. Ventura. HyDR-MI: A Hybrid Algorithm to Reduce
Dimensionality in Multiple Instance Learning. Information Sciences, 222, 282-301, 2013.
[33] C. Romero, P. G. Espejo, A. Zafra, J. R. Romero & S. Ventura. Web Usage Mining for
Predicting Final Marks of MOODLE Students. Computer Applications in Engineering
Education, 21(1), 135-146, 2013.
[34] C. Marquez, A. Cano, C. Romero & S. Ventura. Predicting school failure using a genetic
programming algorithm and different data mining approaches with high dimensional and
unbalanced data. Applied Intelligence, 38, 315-330, 2013.
[35] C. Romero, A. Zafra, J. M. Luna & S. Ventura. Association rule mining for providing feedback
to instructors from multiple-choice quiz data. Expert Systems, 30(2), 162-172, 2013. DOI:
10.1111/j.1468-0394.2012.00627.x
[36] J. M. Luna, J. R. Romero & S. Ventura. Grammar-Based Multi-Objective Algorithms for
Mining Association Rules. Data and Knowledge Engineering, 86, 19-37, 2013. DOI:
10.1016/j.datak.2013.01.002
[37] A. Cano, J.L. Olmo & S. Ventura. Parallel Multi-Objective Ant Programming for Classification
Using GPUs. Journal of Parallel and Distributed Computing, 73(6), 713-728, 2013.
DOI:10.1016/j.jpdc.2013.01.017
[38] A. Zafra, S. Ventura. Multi-instance Genetic Programming for Predicting Student
Performance in Web Based Educational Environments. Applied Soft Computing, 12(8),
2693–2706, 2012. DOI: 10.1016/j.asoc.2012.03.054
[39] J. L. Olmo, J. R. Romero & S. Ventura. Classification rule mining using ant programming
guided by grammar with multiple Pareto Fronts. Soft Computing, 16(12), 2143-2163, 2012.
DOI: 10.1007/s00500-012-0883-8
[40] A. Zafra, M. Pechenizkiy & S. Ventura. ReliefF-MI: An extension of ReliefF to Multiple
Instance Learning. Neurocomputing, Vol. 75(1), 210-218, 2012.
[41] A. Cano, A. Zafra & S. Ventura. Speeding up GP classification algorithms on GPUs. Soft
Computing, 16(2), 187-202, 2012.
[42] A. Zafra & S. Ventura. Multi-Objective Approach Based on Grammar-Guided Genetic
Programming for Solving Multiple Instance Problems. Soft Computing, 16(6), 955-977, 2012.
[43] J.M. Luna, J.R. Romero & S. Ventura. Design and Behavior Study of a Grammar Guided
Genetic Programming Algorithm for Mining Association Rules. Knowledge and Information
Systems, 32(1), 53-76, 2012. DOI: 10.1007/s10115-011-0419-z.
[44] A. Zafra, E. Gibaja & S. Ventura. Multi-instance Learning with Multi-Objective Genetic
Programming for Web Mining. Applied Soft Computing, 11(1), 93-102, 2011.
[45] J. L. Ávila, E. L. Gibaja, A. Zafra & S. Ventura. A Gene Expression Programming Algorithm
for Multi-Label Classification. Journal of Multiple-Valued Logic and Soft Computing, 17(2-3),
183-206, 2011.
[46] E. García, C. Romero, S. Ventura y C. de Castro. A Collaborative Educational Association
Rule Mining Tool. The Internet and Higher Education Journal, 14(2), 77-88, 2011.
[47] C. Romero, J.M. Luna, J. R. Romero & S. Ventura. RM-Tool: A framework for discovering
and evaluating association rules. Advances in Engineering Software, 42(8), 566-576, 2011.
[48] C. Romero & S. Ventura. Preface to the special issue on data mining for personalised
educational systems. User Model User-Adap Inter, 21(1-2), 2011.
[49] A. Zafra, C. Romero & S. Ventura. Multiple Instance Learning for Classifying Students in
Learning Management Systems. Expert Systems with Applications, 38(12), 15020–
15031,2011.
[50] J. L. Olmo, J. R. Romero & S. Ventura. Using Ant Programming Guided by Grammar for
Building Rule-Based Classifiers. IEEE Trans. on Systems, Man and Cybernetics – Part B:
Cybernetics, 41(6), 1585-1599, 2011.