The PhD Programme in Artificial Intelligence (PDAI) at the Universidad Politécnica de Madrid​ (UPM)  is part of the postgraduate programmes on offer at the Escuela técnica superior de ingenieros informáticos.

As its main aim, this phD programe in Artificial Intelligence intends to bestow a better knowledge in research techniques onto students from fields related to Computing Science and Computer Technology in order for them to be able to approach and solve new scientific and technological problems through research in Artificial Intelligence

This general objective can be complemented with an additional goal that is essential for the contents and purpose of this PhD programme, based on the pairing of innovating research and researching innovation. The first goal aims at innovative lines of research that combine the specialised nature of this academic training and the creativity behind original, active and productive researching careers. The second goal leads to the ability to be creative when facing and solving problems through research.

The doctoral student will finalise this process through the writing and defense of a doctoral thesis.

The phD programe in Artificial Intelligence is adapted from what is decreeded in the Royal Decree 99/2011 about the PhD Programme in Artificial Intelligence   offered  by the Polytechnique University of Madrid, already verified according to the Royal Decree 1393/2007 by the Council of Universities from the Ministry of  Education, Culture and Sports (MECD) and and that has been given an Honorauble Mention for Excellence by the Council of Universities from the Ministry of  Education,  Culture  and Sports  from the academic year 2011-2012 to 2013-2014. At the same time, the latter comes from the adaptation to the European Higher  Education Area of the  previous PhD Programme in Artificial Intelligence, organised according to the Royal Decree 778/1998 and imparted until 2009. And this programme, at the same time,  appeared from the conversion of the PhD Programme in "Computing Science and Artificial Intelligence" that had been imparted at the Faculty of Computer Science in the UPM since its creation.The aforementioned programmes received the Quality Award from the Ministry of Education and Science (MCD2005-00352 and MCD2006-00520) in the academic years 1996/97, 2000/01, 2001/02, 2005/06, 2006/07 and 2007/08.



The programme is assigned to the Escuela técnica superior de ingenieros informáticos, placed in the Technology Campus of Montegancedo (I2 Tech Campus) of the Universidad Politécnica de Madrid​ (UPM)  that received the certificate of Campus of International Excellence from the MECD in the application of 2010.

The teaching staff is divided into different groups that develop the following 5 lines of research:

Line 1: Applications of Artificial Intelligence.

  • Medical Informatics.
  • Bioinformatics.
  • Hydroinformatics.
  • Neuroscience.
  • Semantic Web.
  • Internet of the Future.
  • Nanocomputing.

Line 2: Natural Computing.

  • Natural Computing.
  • Bio-inspired Computing.
  • Evolutionary Computation.
  • Synthetic Biology.
  • Biological Systems Engineering.
  • Systems Biology.
  • Biomolecular Computing.
  • DNA Computing.
  • Cellular Programming.

Line 3: Perception, Manipulation y Communication.

  • Human-machine Interaction.
  • Mobile Robotics, Multi-robot And Multi-component Systems.
  • Advanced Control.
  • Cognitive And Bio-inspired Models.
  • Digital Image Processing And Computer Vision.
  • Language Resources.
  • Machine Translation.
  • Information Retrieval And Extraction.
  • Language Engineering.
  • Question-answering systems.


Line 4: Computational Intelligence.

  • Machine Learning.
  • Bayesian Networks.
  • Decision Theory.
  • Multiobjective Optimization.
  • Feature selection.
  • Heuristic Optimization Methods.
  • Estimation Of Distribution Algorithms.

Line 5: Knowledge Representation And Reasoning.

  • Ontology Engineering.
  • Semantic Web.
  • Linked Data.
  • Multilingualism.
  • Logic Models.
  • Description Logic.
  • Extensions Of Classical Logic.
  • Logic Programming.
  • Data Integration.
  • Content Repressentativeness. Application Contexts.
  • Agents and multiagent systems.
  • Fuzzy Logic.
  • Common Sense Reasoning.
  • Qualitative Reasoning.
  • Probabilistic Reasoning.
  • Model-based Reasoning.
  • Non-monotonic Reasoning.