Sebastian Ventura (0000-0003-4216-6378)

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Biography

Sebastian Ventura was born in Cordoba (Spain) in 1966. He received his BSc and PhD degrees in sciences from the University of Cordoba in 1989 and 1996, respectively. He is currently a Full Professor in the Department of Computer Science and Numerical Analysis, University of Cordoba, Deputy Director at the Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), and Head of the "Knowledge Discovery and Intelligent Systems" Research Laboratory at the DaSCI institute. He has authored or co-authored more than 300 international publications. He has also edited several special issues in scientific journals and books in their fields of interest. He has also coordinated about fifteen research projects supported by the Spanish and Andalusian governments, the European Union and other entities. His research interests include machine learning, data mining, computational intelligence, and applications.

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University of Córdoba: Córdoba, Andalucia, ES

2016-04-14 to present | Full Professor (Computer Science and Numerical Analysis)

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Sebastian Ventura

https://orcid.org/0000-0003-4216-6378

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Employment (2)

University of Córdoba: Córdoba, Andalucia, ES

University of Cordoba: Cordoba, Andalucia, ES

Education and qualifications (3)

Polytechnic University of Madrid: Madrid, ES

University of Cordoba: Cordoba, ES

University of Cordoba: Cordoba, ES

Professional activities (4)

Association for Computing Machinery: New York, NY, US

Andalusian Research Institute on Data Science and Computational Intelligence: Granada, Jaén and Cordoba, Andalusia, ES

Virginia Commonwealth University: Richmond, Virginia, US

IEEE: New York, NY, US

Funding (5)

Mejorando la Experiencia del Usuario de Ciencia de Datos con Inteligencia Computacional (INTENSE)

MANPREDIC: Mantenimiento predictivo de plataformas terrestres

EMERging trends in Data analysis (EMERalD)

More Flexible Representations in Data Mining

New Problems in Knowledge Discovery: A Genetic Programming Approach

Works (50 of 135)

Facing Up Fare War: Generating Competitive Price Models With Gene Expression Programming

Reducing the Label Space a Predefined Ratio for a More Efficient Multilabel Classification

Data mining in predictive maintenance systems: A taxonomy and systematic review

An ensemble-based convolutional neural network model powered by a genetic algorithm for melanoma diagnosis

Course Recommendation based on Sequences: An Evolutionary Search of Emerging Sequential Patterns

Smart Operators for Inducing Colorectal Cancer Classification Trees with PonyGE2 Grammatical Evolution Python Package

Modeling and predicting students’ engagement behaviors using mixture Markov models

Improving the understanding of cancer in a descriptive way: An emerging pattern mining‐based approach

Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers

Subgroup discovery in MOOCs: a big data application for describing different types of learners

Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules

Classification Accuracy of Hepatitis C Virus Infection Outcome: Data Mining Approach

Mining local periodic patterns in a discrete sequence

Exceptional in so Many Ways—Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios

Extracting User-Centric Knowledge on Two Different Spaces: Concepts and Records

Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization

Splicing machinery dysregulation drives glioblastoma development/aggressiveness: oncogenic role of SRSF3

Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms

Educational data mining and learning analytics: An updated survey

Classification Accuracy of Hepatitis C Virus Infection Outcome: Data Mining Approach (Preprint)

Distributed Selection of Continuous Features in Multilabel Classification Using Mutual Information

Evaluating associative classification algorithms for Big Data

Frequent itemset mining: A 25 years review

An evolutionary approach to build ensembles of multi-label classifiers

WordificationMI: multi-relational data mining through multiple-instance propositionalization

A Grammar-Guided Genetic Programing Algorithm for Associative Classification in Big Data

Distributed nearest neighbor classification for large-scale multi-label data on spark

Interactive multi-objective evolutionary optimization of software architectures

MIRSVM: Multi-instance support vector machine with bag representatives

Evolutionary Strategy to Perform Batch-Mode Active Learning on Multi-Label Data

OLLAWV: OnLine Learning Algorithm using Worst-Violators

Statistical comparisons of active learning strategies over multiple datasets

Effective active learning strategy for multi-label learning

Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming

Exhaustive search algorithms to mine subgroups on Big Data using Apache Spark

MLDA: A tool for analyzing multi-label datasets

Multiple Instance Learning: Foundations and Algorithms

Speeding-Up Association Rule Mining With Inverted Index Compression

An ensemble-based approach for multi-view multi-label classification

Discovering useful patterns from multiple instance data

Effective lazy learning algorithm based on a data gravitation model for multi-label learning

Pattern Mining with Evolutionary Algorithms

LAIM discretization for multi-label data

A Tutorial on Multilabel Learning

An approach for the evolutionary discovery of software architectures

An evolutionary algorithm for the discovery of rare class association rules in learning management systems

Multi-objective genetic programming for feature extraction and data visualization

Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context

Evolutionary feature weighting to improve the performance of multi-label lazy algorithms