The group aims to explore the synergy between machine learning and optimization to achieve collaborative effects in building highly efficient and smart systems.
Our methodological research concerns: metaheuristics for learning, data driven learning in optimization, real-time learning, data reduction and feature mining, learning and optimization under uncertainty.
We are also actively engaged in practical applications, to test and apply the new developed methods and algorithms in current challenging scenarios such as industrial or biomedical ones. The interesting application areas include (yet are not limited to) the following:
|First Name||Last Name||Title|
|Miguel||Leon Ortiz||Doctoral student|
|ADAPTER: Adaptive Learning and Information Fusion for Online Classification Based on Evolving Big Data Streams||active|
|Digitalization of HVDC grids by means of smart data discovery||active|
|Machine learning in power devices and power systems||active|
|Computational Intelligence in Process Modelling and Prediction||finished|
|EMOPAC - Evolutionary Multi-Objective Optimization and Its Applications in Analog Circuit Design||finished|
A Neural Network for Stance Phase detection in smart cane users (Jun 2019) Juan Rafael Caro-Romero , Joaquin Ballesteros, Francisco Garcia-Lagos , Francisco Sandoval 15th International Work-Conference on Artificial Neural Networks (IWANN'19)
Feature Selection of EEG Oscillatory Activity Related to Motor Imagery Using a Hierarchical Genetic Algorithm (Jun 2019) Miguel Leon Ortiz, Joaquin Ballesteros, Jonatan Tidare, Ning Xiong, Elaine Åstrand IEEE Congress on Evolutionary Computation (IEEE CEC'19)
Discriminating EEG spectral power related to mental imagery of closing and opening of hand (Mar 2019) Jonatan Tidare, Miguel Leon Ortiz, Ning Xiong, Elaine Åstrand THe 9th International IEEE EMBS Conference of Neural Engineering (IEEE NER'19)
Improved Vine Copula-Based Dependence Description for Multivariate Process Monitoring based on Ensemble Learning (Feb 2019) Yang Zhou, Shaojun Li, Ning Xiong Industrial & Engineering Chemistry Research (IECR'19)
Unbounded Sparse Census Transform using Genetic Algorithm (Jan 2019) Carl Ahlberg, Miguel Leon Ortiz, Fredrik Ekstrand, Mikael Ekström WACV 2019 - IEEE Winter Conference on Applications of Computer Vision (WACV'19)