My PhD Thesis, entitled "Multi-Agent System to model Consensus Processes in Large-Scale Group Decision-Making using Soft Computing Techniques" was completed and defended in the University of Jaén (Spain) in 2014, as a compendium of published journal articles, obtaining the distinction of Excellent Cum Laude by unanimity, and the special mention of "International PhD". A pdf copy of my PhD dissertation is available for download here (an English summary is available in Appendix A, along with original publications in Chapter 4).



  • Decision-Making and Decision Support Systems under Uncertainty
  • Recommender Systems: collaborative filtering, intelligent data fusion, security aspects
  • Autonomous Intelligent (Multi-Agent) Systems
  • Data Science with Applications to Data-Driven Decision Support and Autonomous Decision-Making

Below I list in more detail the main lines of investigation I am interested in. Whilst I have undertaken some deal of research in many of the topics enumerated, there are a few other topics in which I am highly interested and familiarised with, hence they deserve a place in the list as well. If your work covers any of these topics or other similar ones, please get in touch and drop me an e-mail: I'd be happy to hear about you and your work!

Intelligent Decision Support Systems

Decision Making under Uncertainty · Group decision making · Multi-criteria decision making · Large-group decision making · Consensus support · Consensus measurement and reaching · Preference modeling · Fuzzy and linguistic decision making · Decision Support Systems · Aggregation processes in DM · Intelligent Decision Technologies

Recommender Systems

Collaborative Filtering · Hybrid Recommender Systems · Resilience in Recommender Systems · Multi-view information aggregation · Intelligent similarity and aggregation methods · Group Recommender Systems · Uncertain data handling in Recommender Algorithms · Innovative applications (tourism and volunteering platforms, citizen wellbeing, scalable smart city services, crowdfunding and crowdsourcing systems, shared economy, global e-learning platforms)

Data Science: Uncertain Information Management, Knowledge Modelling and Data Fusion

Applications: Cyber-Security, SCADA systems, supply chain management · AI techniques in Data Science · Data-driven decision support · Theories of Uncertainty (belief theory, probabilistic/possibilistic/fuzzy) · Knowledge extraction · Knowledge Engineering · Modeling imprecision and vagueness · Situational Awareness · Sensor Data Fusion · Streaming Data Analytics · User Behavior Analytics · Unsupervised learning · Big Data tools

Autonomous Intelligent Systems and Collaborative Multi-Agent Planning

Multi-Agent Systems · Agent-based modelling · Automated Planning · Planning under Uncertainty · Team planning · Collaborative aspects of agent planning · Coordination, negotiation and argumentation · Agent reasoning/inference for decision-making · Evidential reasoning · Reinforcement learning · Approximate algorithms · Agent-based simulation · Human cognitive aspects emulation · Hybrid human-agent collaborative systems


Recently, I have been investigator in the following UK and EU projects:
  • Intelligent Decision-Making and Big Data Fusion Strategies in Recommender Systems: application to Point-of-Interest and Leisure Recommendation in Smart Cities   (ongoing)Recommender Systems (RS) provide users with tailored information to meet their needs in contexts of information overload. They help “matching the right user with the right products/services at the right time”. Multi-view RS models exploit and combine multiple sources of heterogeneous data (user preferences, profile, contextual information, social trust, text reviews) across recommendation processes to provide end users with improved personalization services. This project aims at taking a novel and revolutionary step forward in the state-of-the-art of RS modeling, and its application in nowadays data-pervaded domains, with a focus on personalization for tourism and leisure in smart cities.
  • CSIT 2 (Centre for Secure Information Technologies):  I currently undertake research and proof-of-concept development activities on Data Analytics and Decision Support approaches for cyber-security challenges. Namely, some of my lines of work in this context include: (1) combining Big Data Analytics tools with intelligent multi-criteria decision support methods to enhance monitoring of user behavior data, with application to insider threats; (2) supporting in producing proof-of-concept demonstrator material on evidential reasoning approaches to deal with uncertainty of data in Intrusion Detection Systems (IDS); (3) agent-based modeling and reinforcement learning approaches to simulate and generate meaningful user activity data for its use in User Behavior Analytics (UBA) testbeds via Big Data tools.
  • PACES (Providing Autonomous Capabilities for Evolving SCADA): This project funded by EPSRC focused on developing next generation SCADA systems based on autonomous and intelligent capabilities. My role focused on defining and developing multi-agent systems architectures. In particular, I collaborated in defining extended BDI agent frameworks to incorporate reasoning under uncertainty, and studied collaboration aspects of multi-agent planning approaches under uncertainty. As a result, we defined two novel multi-agent planning approaches in environments pervaded by uncertainty/risk, incorporating (i) a two-stage method based on subgoal delegation in agent teams as a means of coordination, and (ii) a risk-aware multi-agent planner that combines planning at team level with multi-criteria and consensus decision-making methodologies to collectively select the "best" actions, predicated on the distinct agents' attitudes towards risk. In addition, I developed a visual demonstrator (envisaged as a videogame-like interface) to showcase autonomous agents with risk-aware planning, reasoning and decision making capabilities.
  • COBACORE (Community-based Comprehensive Recovery)In this FP7 EU Project focused on comprehensive disaster management and recovery, I applied semantic inference and multi-criteria decision making approaches to construct a need-capacity matching algorithm to assist affected and responding communities after a disaster with filtering of relevant resources for time-sensitive decision-making.
  • BESECURE (Best Practice Enhancers for Security in Urban Regions)In this FP7 EU Project, I worked on a GIS-based Web platform to provide a variety of descriptors based on disparate urban data across multiple dimensions, including crime, economic, societal and educational data.
NOTE: All of the three EU FP7 Projects above were scoped under the "Secure Societies" H2020 programme.

This is my "virtual bookshelf", containing both recent and (in my opinion) state-of-the-art handbooks, related to my research interests, in alphabetical author order:
  • C.C. Aggarwal. Recommender Systems: the Textbook. 1st Ed. Springer, 2016.
  • I. Alsmadi, F. Karabatis, A. Al-Eroud (Eds.). Information Fusion for Cyber-Security Analytics. Studies in Computational Intelligence, vol. 691. Springer, 2016.
  • Rajendra Akerkar, Priti Srinivas Sajja. Intelligent Techniques for Data Science. 1st Ed. Springer, 2016.
  • A. Appriou. Uncertainty Theories and Multisensor Data Fusion. Wiley, 2014.
  • Gleb Beliakov, Ana Pradera, Tomasa Calvo. Aggregation Functions - A Guide for Practitioners. 1st Ed. reprint. Springer, 2010.
  • Tomasa Calvo, Joans Torrens (Eds.). Fuzzy Logic and Information Fusion: to Conmemorate the 70th birthday of Professor Gaspar Mayor. Studies in Fuzziness and Soft Computing, vol. 339. Springer, 2016.
  • Vladimir Cherkassky. Learning from Data: Concepts, Theory and Methods. 2nd Ed. Wiley-blackwell, 2007.
  • Y. Dong, J. Xu (Eds.). Consensus Building in Group Decision Making: searching the consensus path with minimum adjustments. Springer, 2016.
  • Michael Doumpos, Evangelos Grigoroudis. Multicriteria Decision Aid and Artificial Intelligence. Wiley, 2013.
  • A. Felferning, L. Boratto, M. Stettinger, M. Tkalcic. Group Recommender Systems: An Introduction. Springer, 2018.
  • János Fodor, Marc Roubens. Fuzzy Preference Modelling and Multicriteria Decision Support. Theory and Decision Library, vol. 14. Springer, 1994.
  • Malik Ghallab, Dana Nau, Paolo Traverso. Automated Planning and Acting. Cambridge University Press, 2016.
  • Mohammed Guller. Big Data Analytics with Spark. A practitioners guide to using Spark for Large Scale Data Analytics. Apress, 2015.
  • M.J. Kochenderfer. Decision Making under Uncertainty: Theory and Application. MIT Lincoln Laboratory Series, The MIT Press, 2015.
  • Weiru Liu. Propositional, Probabilistic and Evidential Reasoning: Integrating Numerical and Symbolic Approaches. Studies in Fuzziness and Soft Computing, vol. 77. Springer-Verlag, 2011.
  • Jie Lu et al. Multi Objective Group Decision Making: Methods, Software and Applications with Fuzzy Set Techniques. Imperial College Press, 2006.  
  • Stuart Russell. Artificial Intelligence: A Modern Approach., 3rd Ed. Pearson, 2016.
  • Richard Sutton. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning Series). The MIT Press, 1998.
  • Gerhard Weiss. MultiAgent Systems (Intelligent Robotics and Autonomous Systems Series), 2nd Ed. The MIT Press, 2013. 
  • K. Wirth, K. Sweet. One-to-One Personalization in The Age of Machine Learning. Bookbaby, 2017.
  • Michael Wooldridge. An Introduction to Multi-Agent Systems, 2nd Ed. Wiley, 2009.
  • Constantin Zopounidies, Michael Doumpos (Eds.). Multiple Criteria Decision Making: Applications in Management and Engineering. 1st Ed. Springer, 2017.
For sure I may miss some interesting books in this list. If you would like to suggest any, I will appreciate if you contact me, as I am always keen on getting to know new, or yet unknown books.
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