The Applied Intelligence & Data Analysis (AIDA) interest group is focused in the following research lines:
  • Basic Research
    • Machine Learning: mainly focused on unsupervised learning (Clustering and Hidden Markov Models). Nevertheless, we have also worked in the application of evolutionary computing (boosting) and Deep Learning (Convolutional Neural Networks) to supervised classification problems.
    • Evolutionary computation: mostly centered on mono and multi-objective Genetic Algorithms and Genetic Programing.
    • Social Network Analysis (SNA): application of AI and Machine Learning techniques to solve problems in complex networks, pattern recognition, development of new SNA algorithms, analysis of SNA technology… etc.
    • Swarm Intelligence: Mostly focused on the study of Ant Colony Optimization(ACO) algorithms.
    • Decision Support Systems: manly geared towards the design of man-in-the-loop information system for decision making in high complexity domains (aeronautics, aerospace, mining, medicine …etc)
    • Constraint Programing: mostly focused on the hybridization of classical Constraint Programming techniques with Evolutionary and Swarm Intelligence algorithms for solving Constraint Satisfaction Problems (CSP) for planning and resource allocation.
    • Graph Computing: we design evolutionary and swarm intelligence algorithms for community detection in complex networks.
  • Applied research
    • Social media (Radicalization and hate speech, polarization, politics, marketing…etc).
    • Malware detection and analysis.
    • Aerospace 
    • Unmanned Air Vehicles and Systems (UAV/UAS).
    • Industry (mining, metallurgy, logistics, transports…etc).
    • Video-games and serious games.
  • Research Areas reports