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Professor Francisco Chiclana

Job: Professor of Computational Intelligence and Decision Making

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Research group(s): Center for Computational Intelligence (CCI)

Address: De Montfort University, The Gateway, Leicester, LE1 9BH UK

T: +44 (0)116 207 8413

E: chiclana@dmu.ac.uk

W: http://www.tech.dmu.ac.uk/~chiclana/

 

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Personal profile

Professor Francisco Chiclana received the B.Sc. and Ph.D. degrees in Mathematics, both from the University of Granada (Spain) in 1989 and 2000, respectively. He is currently a Professor of Computational Intelligence and Decision Making, and founder of DIGITS - De Montfort University Interdisciplinary Group in Intelligent Transport Systems, Faculty of Technology, De Montfort University (Leicester, UK). 

Professor Francisco Chiclana was the Coordinator of DMU submission for REF 2014 UOA 11: Computer Science and Informatics. 

Professor Chiclana has been Deputy Course Leader of the MScs in Computing, Information Technology, and Information Systems Management; Programme Tutor Years 1 and 2 of the BSc/HND/FD Business Information Technology. In 2013, Professor Chiclana co-developed the Doctoral Training Programme (DTP) in Intelligent Systems (IS) that he presently co-leads. Currently, he is Course Leader of BSc/MCOMP in Intelligent Systems (IS) and of MSc IS/ IS & Robotics (ISR).

Research group affiliations

Publications and outputs

  • A Confidence and Conflict-based Consensus Reaching Process for Large-scale Group Decision Making Problems with Intuitionistic Fuzzy Representations
    dc.title: A Confidence and Conflict-based Consensus Reaching Process for Large-scale Group Decision Making Problems with Intuitionistic Fuzzy Representations dc.contributor.author: Ding, Ru-Xi; Yang, Bing; Yang, Guo-Rui; Li, Meng-Nan; Wang, Xueqing; Chiclana, Francisco dc.description.abstract: With the development of social democracy, the public begin to participate in large-scale group decision making (LSGDM) events that have a significant impact on their personal interests. However, the participation of the public with insufficient expertise will cause much hesitancy in the evaluations of decision makers (DMs), which can be captured by intuitionistic fuzzy sets. Meanwhile, due to the increment in the number of DMs, the cost of consensus reaching processes (CRPs), which are utilized to help DMs reach a consensus, is getting higher and higher. In order to improve the efficiency of the CRP, this paper presents a confidence and conflict-based consensus reaching process (CC-CRP) for LSGDM events with intuitionistic fuzzy representations. In the proposed model, according to the hesitancy of the DMs’ intuitionistic fuzzy evaluations, an objective method is firstly developed to calculate the confidence level of DMs that does not require any extra information. Then, a three-dimension clustering method is designed by considering the type of conflict, the degree of conflict, and the confidence level of DMs. After this, an efficiency rate of modification is defined to select DMs who will be persuaded first to adjust their evaluations with recommendation plans generated by a specific optimal method. Finally, according to the clustering process results, different CC-CRP management methods will apply to DMs with different attributes. An illustrative example and several experiments are reported to provide evidence that the proposed model is feasible and effective. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • An integrated decision framework for evaluating and recommending health care services
    dc.title: An integrated decision framework for evaluating and recommending health care services dc.contributor.author: Alshouha, Bashar; Serrano-Guerrero, Jesus; Chiclana, Francisco; Romero, Francisco P.; Olivas, Jose A. dc.description.abstract: Quality management techniques such as the quality function deployment model can help hospitals assess and improve the quality of their services by integrating the voice of customers. The different quality parameters of this model are usually determined and assessed by experts; nonetheless, obtaining such experts is not always easy or inexpensive. Moreover, in this method, patient opinions are not usually considered directly, although they are the real users of the services and those who can best assess those services. Nevertheless, these opinions are easily accessible today, owing to the development of medical social networks where patients directly convey their opinions about the different services and features of a hospital. Therefore, it is feasible to replace expert knowledge with the information provided by these opinions. Based on this idea, this study proposes a novel fuzzy recommendation model based on the quality function deployment method to rank hospitals depending on patient opinions and preferences regarding hospital services. This model integrates a topic modeling strategy for determining hospital requirements, customer needs, and the relationship between them as well as a sentiment analysis algorithm for assessing customer satisfaction regarding hospital services. To demonstrate the usefulness of the proposed method, several experiments were conducted using patient reviews from real hospitals, and the method was compared against other recommendation models. The results prove that this approach represents a step toward more personalized and effective health care system selection considering patient preferences and opinions. dc.description: open access article
  • A bilateral negotiation mechanism by dynamic harmony threshold for group consensus decision making
    dc.title: A bilateral negotiation mechanism by dynamic harmony threshold for group consensus decision making dc.contributor.author: Cao, Mingshuo; Chiclana, Francisco; Liu, Yujia; Wu, Jian; Herrera-Viedma, Enrique dc.description.abstract: This article proposes a framework for bilateral negotiation mechanism to deal the case the concordant decision-makers (DMs) coalition cannot be constructed, which resolves the limitations of the existing group decision making methods. Bilateral negotiation means a process in which any two involved DMs change their own opinions based on each other’s opinions, avoiding the formation of group coalitions and the coercion of individual DMs. It can not only improve group consensus by interaction between individual DMs, but also considers the limited compromise behavior of DMs in the consensus bargaining process. The key contributions of this article contain: (1) It investigates the concept of ‘harmony threshold’ by combining the consensus levels of individual DMs and the number of group members to explain the limited compromise behavior of DMs. (2) it proposes a novel bilateral negotiation consensus mechanism with personalized compromise behavior with the group consensus threshold as the objective function and personalized harmony thresholds as constraints to help any two discording DMs partly to adopt each other’s opinions. And (3) It develops the ranking difference level (RDL) to measure the deviation degree between the final ranking of alternatives and all the DMs’ original rankings of alternatives. The research found that the proposed mechanism can reduce consensus cost by 40% and ranking difference by 5%. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Profiling Social Sentiment in Times of Health Emergencies with Information from Social Networks and Official Statistics
    dc.title: Profiling Social Sentiment in Times of Health Emergencies with Information from Social Networks and Official Statistics dc.contributor.author: Velasco-López, Jorge-Eusebio; Carrasco, Ramón-Alberto; Serrano-Guerrero, Jesús; Chiclana, Francisco dc.description.abstract: Social networks and official statistics have become vital sources of information in times of health emergencies. The ability to monitor and profile social sentiment is essential for understanding public perception and response in the context of public health crises, such as the one resulting from the COVID-19 pandemic. This study will explore how social sentiment monitoring and profiling can be conducted using information from social networks and official statistics, and how this combination of data can offer a more complete picture of social dynamics in times of emergency, providing a valuable tool for understanding public perception and guiding a public health response. To this end, a three-layer architecture based on Big Data and Artificial Intelligence is presented: the first layer focuses mainly on collecting, storing, and governing the necessary data such as social media and official statistics; in the second layer, the representation models and machine learning necessary for knowledge generation are built, and in the third layer the previously generated knowledge is adapted for better understanding by crisis managers through visualization techniques among others. Based on this architecture, a KDD (Knowledge Discovery in Databases) framework is implemented using methodological tools such as sentiment analysis, fuzzy 2-tuple linguistic models and time series prediction with the Prophet model. As a practical demonstration of the proposed model, we use tweets as data source (from the social network X, formerly known as Twitter) generated during the COVID-19 pandemic lockdown period in Spain, which are processed to identify the overall sentiment using sentiment analysis techniques and fuzzy linguistic variables, and combined with official statistical indicators for prediction, visualizing the results through dashboards. dc.description: open access article
  • Artificial Intelligence in Science: Shut up and Calculate
    dc.title: Artificial Intelligence in Science: Shut up and Calculate dc.contributor.author: Carrasco, Ramon A.; Arias-Oliva, Mario; Serrano-Guerrero, J.; Chiclana, Francisco
  • Evolution of Credit Scores of Enterprises in a Social Network: A Perspective Based on Opinion Dynamics
    dc.title: Evolution of Credit Scores of Enterprises in a Social Network: A Perspective Based on Opinion Dynamics dc.contributor.author: Liang, Haiming; Xu, Weijun; Chiclana, Francisco; Yu, Shui; Dong, Yucheng; Herrera-Viedma, Enrique dc.description.abstract: The use of social network to model the evolution of credit scores of networked enterprises is still a challenging task. This article develops an opinion dynamics model of the evolution of credit scores of enterprises in a social network. Firstly, based on the number of potential cooperated enterprises and the initial credit scores, the leader and follower enterprises are identified. Then, taking into consideration the cooperated benefit and discrimination cost, the cooperated utility between any two enterprises is calculated, which is used to compute the weights that one enterprise assigns to other enterprises. An opinion dynamics model on the evolution of credit scores of enterprises, inspired on the classical Friedkin–Johnsen’s social network model, is developed. Some desirable properties of the proposed opinion dynamics model are theoretically stated and proved. Finally, a numerical example is provided to illustrate the feasibility of the proposed opinion dynamics model, while a simulation analysis to investigate the joint influences of the connection probabilities and the network structure on the evolution of credit scores of enterprises is reported. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Managing heterogeneous preferences and multiple consensus behaviors with self-confidence in large-scale group decision making
    dc.title: Managing heterogeneous preferences and multiple consensus behaviors with self-confidence in large-scale group decision making dc.contributor.author: Liu, Wenqi; Wu, Yuzhu; Chen, Xin; Chiclana, Francisco dc.description.abstract: With the rapid increase of experts, groups or organizations involved in decision making, the problem of large-scale group decision making (LSGDM) has attracted increasing attention in the whole research field. Behavioral management and heterogeneous preference representation structures are two fundamental aspects of LSGDM problems. However, psychological functioning has been less considered in existing consensus models to deal with the different behavioral styles of decision-makers. Therefore, this study proposes a novel consensus reaching framework to detect and manage multiple styles of behavior in LSGDM based on heterogeneous preferences with self-confidence. Specifically, an optimization-based selection process is introduced to obtain the individual and collective preference vectors. Next, a self-confidence driven consensus approach is proposed, which includes consensus measure, clustering, detection of multiple styles of behavior, and hybrid feedback adjustment mechanism. According to the consensus level and the self-confidence level, the proposed detection of multiple styles of behavior method identifies four different behavioral subgroup types: collaborating, accommodating, competing, and avoiding. The hybrid feedback adjustment mechanism generates different feedback adjustment opinions for the four identified behavioral type subgroups. The effectiveness and characteristics of the proposed consensus approach is demonstrated with an emergency management case study and the reporting of comprehensive simulation experiments. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • BioEmoDetector: A flexible platform for detecting emotions from health narratives
    dc.title: BioEmoDetector: A flexible platform for detecting emotions from health narratives dc.contributor.author: Alshouha, Bashar; Serrano-Guerrero, Jesus; Chiclana, Francisco; Romero, Francisco P.; Olivas, Jose A. dc.description.abstract: Emotion detection can play a pivotal role in healthcare. Many psychological/psychical illnesses and disorders such as depression, anxiety, or emotional crises can be explained through the study of different emotional changes suffered by a user. One of the mechanisms to detect these emotional changes is the analysis of the user’s expressions/conversations, which can be easily represented as texts. Therefore, it is necessary to count on tools able to recognize and measure the intensity of these emotions. In this sense, at the present moment biomedical and clinical pre-trained language models have been extensively used for text classification tasks; nevertheless, their applications to the field of emotion classification, specially in healthcare, remain relatively unexplored. For that reason, this paper presents BioEmoDetector, an open-source framework for emotion prediction from texts related to medical environments. This tool introduces a flexible framework leveraging multiple biomedical and clinical pre-trained language models which can work individually or together under an ensemble model. This approach provides a powerful tool for understanding the patients’ experiences through their conversations and their impact on health outcomes. dc.description: open access article
  • Global feedback mechanism by explicit and implicit power for group consensus in social network
    dc.title: Global feedback mechanism by explicit and implicit power for group consensus in social network dc.contributor.author: Wang, Sha; Wu, Jian; Chiclana, Francisco; Ji, Feixia; Fujita, Hamido dc.description.abstract: This paper investigates a global feedback consensus model which determines the importance of decision makers by combining explicit and implicit Power. Explicit power is obtained according to the differences in organizational hierarchy, while implicit power manifests itself by being recognized in social network interaction. Combining these two types of power, an approach is proposed to characterize the binary power of decision makers jointly to identify the key decision units. Then, a global feedback mechanism based on the binary power is investigated. Its innovation is that it searches the adjustors who are most conducive to achieve group consensus in global and implement personalized feedback services to achieve the minimum cost optimization goal. Finally, an illustrative example to verify the validity of the proposed method are reported.
  • Personality Trait Detection via Transfer Learning
    dc.title: Personality Trait Detection via Transfer Learning dc.contributor.author: Alshouha, Bashar; Serrano-Guerrero, Jesus; Chiclana, Francisco; Romero, Francisco P.; Olivas, Jose A. dc.description.abstract: Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains, including education, e-commerce, or human resources. Traditional machine learning techniques have been broadly employed for personality trait identification; nevertheless, the development of new technologies based on deep learning has led to new opportunities to improve their performance. This study focuses on the capabilities of pre-trained language models such as BERT, RoBERTa, ALBERT, ELECTRA, ERNIE, or XLNet, to deal with the task of personality recognition. These models are able to capture structural features from textual content and comprehend a multitude of language facets and complex features such as hierarchical relationships or long-term dependencies. This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs. The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts. Moreover, it is able to fine-tune the previous models using the MyPersonality dataset, which comprises 9,917 status updates contributed by 250 Facebook users. These status updates are categorized according to the well-known Big Five personality model, setting the stage for a comprehensive exploration of personality traits. To test the proposal, a set of experiments have been performed using different metrics such as the exact match ratio, hamming loss, zero-one-loss, precision, recall, F1-score, and weighted averages. The results reveal ERNIE is the top-performing model, achieving an exact match ratio of 72.32%, an accuracy rate of 87.17%, and 84.41% of F1-score. The findings demonstrate that the tested models substantially outperform other state-of-the-art studies, enhancing the accuracy by at least 3% and confirming them as powerful tools for personality recognition. These findings represent substantial advancements in personality recognition, making them appropriate for the development of user-centric applications. dc.description: open access article


Click here to view a full listing of Francisco Chiclana's publications and outputs.

Key research outputs

F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera: Cardinal Consistency of Reciprocal Preference Relations: A Characterization of Multiplicative Transitivity. IEEE Transactions on Fuzzy Systems 17 (1), 14-23, February 2009. doi:10.1109/TFUZZ.2008.928597

S. -M. Zhou, F. Chiclana, R. I. John, J. M. Garibaldi: Type-1 OWA Operators for Aggregating Uncertain Information with Uncertain Weights Induced by Type-2 Linguistic Quantifiers. Fuzzy Sets and Systems 159 (24), 3281-3296, December 2008. doi:10.1016/j.fss.2008.06.018 

S-M. Zhou, F. Chiclana,R. John, J. M. Garibaldi: Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments. IEEE Transactions on Knowledge and Data Engineering 23 (10) 1455-1468, October 2011. doi: 10.1109/TKDE.2010.191

F. Herrera, E. Herrera-Viedma, S. Alonso, F. Chiclana: Computing with Words in Decision Making: Foundations, Trends and Prospects. Fuzzy Optimization and Decision Making 8, 337-364, 2009 (ISSN: 1568-4539). doi: 10.1007/s10700-009-9065-2

Patrizia Pérez-Asurmendi, F. Chiclana: Linguistic majorities with difference in support. Applied Soft Computing 18, May 2014, Pages 196–208. doi: 10.1016/j.asoc.2014.01.010

F. Chiclana, J. M. Tapia-Garcia, M. J. del Moral, E. Herrera-Viedma: A Statistical Comparative Study of Different Similarity Measures of Consensus in Group Decision Making. Information Sciences 221, 110-123, February 2013, doi: 10.1016/j.ins.2012.09.014

Jian Wu, F. Chiclana: A social network analysis trust-consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations. Knowledge-Based Systems 59, March 2014, Pages 97–107. doi: 10.1016/j.knosys.2014.01.017

S. Greenfield, F. Chiclana, S. Coupland, R. I. John: The Collapsing Method of Defuzzification for Discretised Interval Type-2 Fuzzy Sets. Information Sciences 179(13), 2055-2069, June 2009. doi: 10.1016/j.ins.2008.07.011

S. Greenfield, F. Chiclana, R. John, S. Coupland: The Sampling Method of Defuzzification for Type-2 Fuzzy Sets: Experimental Evaluation. Information Sciences 189, 77-92, April 2012. doi: 10.1016/j.ins.2011.11.042

E. Herrera-Viedma, F. Herrera, F. Chiclana , M. Luque: Some Issues on Consistency of Fuzzy Preference Relations. European Journal of Operational Research 154(1), 98-109, April 2004. doi:10.1016/S0377-2217(02)00725-7

F. Chiclana, F. Herrera, E. Herrera-Viedma: Integrating Three Representation Models in Fuzzy Multipurpose Decision Making Based on Fuzzy Preference Relations. Fuzzy Sets and Systems 97(1), 33-48, July 1998. doi:10.1016/S0165-0114(96)00339-9 

Research interests/expertise

Fuzzy preference modelling, decision making problems with heterogeneous fuzzy information, decision support systems, the consensus reaching process, recommender systems, social networks, modelling situations with missing/incomplete information, rationality/consistency, intelligent mobility and aggregation of information. 

Areas of teaching

I have a lot of teaching experience that I have acquired over the past 21 years as a secondary school teacher of mathematics (Granada, Montoro-Cordoba, Estepona and Mabella - Malaga) in Spain (September 1990 - July 2003), and at De Montfort University (August 2003 - present) lecturing different modules at undergraduate, postgraduate (MSc) and PhD levels (see list below). Previously, I worked as a temporary lecturer at the Department of Algebra, University of Granada, in Spain (January 1990-March 1990) teaching calculus and financial mathematics to first year students of management studies.

In June 2005, I completed the HEA accredited programme for staff new to teaching in Higher Education which entitled me to registered practitioner status of the Higher Education Academy. Certificate presentation was on 28th September 2005 by the Director of Human Resources. I was glad to have Dr Jenny Carter as my mentor during my first 2 years at DMU. Currently, I am a fellow of the Higher Education Academy.

I was nominated by students for a Vice-Chancellor's Distinguished Teaching Award in 2009. The students think highly of me and my contribution to the student experience is valued as the following quotation testifies:

"He willingly devotes time to listen to any student and has helped me to achieve good mark. He is consistently excellent communicator, stimulating and informative..."         

 

Areas of Teaching:
  • Mathematics for Computing
  • Financial Mathematics
  • Statistics
  • Research Methods
  • Fuzzy Logic

 

Qualifications

  • Certificate Successful completion of HEA accredited pathway for staff new to teaching in Higher Education, De Montfort University, Leicester, UK (September 2005)
  • Outstanding Award for a PhD in Mathematics for the academic year 1999/2000, University of Granada, Spain (27 November 2002)
  • PhD in Mathematics (Distinction Cum Laude), Department of Computer Science and Artificial Intelligence, University of Granada, Spain (24 March 2000)
  • Public examination to become part of government civil service as a secondary school teacher, Ministry of Education and Science, Spanish Government (July 1990)
  • Degree in Mathematics (Statistics & Operational Research), University of Granada, Spain (1984-1989)
  • Certificate of Pedagogic Aptitude, Institute of Educational Science, University of Granada, Spain (1989).

Courses taught

Undergraduate

CSCI1004 - Mathematics for Computing (2003-2004)
MGSC1102 - Modelling for Management Decisions 1 (2003-2004)
INFO1007 - Introduction to Business Computing (2003-2004)
INFO1407 - Introduction to Business Computing (2004-2007)
MATH2211 - Information Systems (2003-2005)
COMP2006 - Research in Computing (2004-2008)
CSCI1412 - Computer Technology (2007-2010)
Industrial Placement Visit Tutor (2003-2012)
IMAT1901: Quantitative Methods (2010-2012)
IMAT2701: HND BIT Project (2009-2012)
IMAT3451 - Final Year Project Supervisor (2003-2012)

Postgraduate

IMAT5119 - Fuzzy Logic (2004-2012)
IMAT5120 - Research Methods (2004-2012)
IMAT5314 - MSc Project (2010-2012)

PhD Level

PhD Course: Typesetting Documents with LaTeX (2004-2012)  

Honours and awards

Outstanding Award for a PhD in Mathematics for the academic year 1999/2000, University of Granada, Spain (27 November 2002).

Third prize in DMU’s Creative Thinking Awards 2010, for the Greenfield-Chiclana Collapsing Defuzzifier.

Finalist for 1st DMU - THE OSCAR AWARDS  in category: Outstanding Contribution to Research Excellence (2012).

Membership of external committees

Fellow of the Higher Education Academy, UK

Member of the European Society for Fuzzy Logic and Technology (EUSFLAT) 

Current research students

Current:

  • Maria Raquel Ureña Perez, University of Granada (Spain)- Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada. January 2012. Co-supervisor: Prof. Enrique Herrera-Viedma
  • Manal Alghieth (DMU) - Second supervisor. First supervisor: Dr Yingjie Yang (CCI). Mode of study: Full -time on site (01/04/2012)
  • Simon Witheridge (DMU) - Intelligent Transport Systems: Integrated Traffic Management Control. First supervisor. Second supervisors: Dr Benjamin Passow (DIGITS) and Dr David Elizondo (DIGITS). Mode of study: Full -time on site (01/10/2012). Change to second supervisor and Ben Passow first supervisor from 01-October-2013.
  • Eseosa Oshodin (DMU) - Decentralised Mechanism for REcommender/Reputation System: A Case Study on Trust. First supervisor. Second supervisors: Dr Samad Ahmadi (VirAL/CCI). Mode of study: Full -time on site (01/10/2013).
  • Salim Hasshu (DMU) - Smart, Green and Integrated Transport - Personalised traffic health planner. First supervisor. Second supervisors: Dr Benjamin Passow (DIGITS) and Dr David Elizondo (DIGITS). Mode of study: Full -time on site (01/10/2013).

Completed:

  • Dr Sergio Alonso Burgos, University of Granada (Spain)- Group Decision Making With Incomplete Fuzzy Preference Relations. Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada. May 2006. Co-supervisors: Prof. Enrique Herrera-Viedma, Prof. Francisco Herrera.
  • Dr Fahad Alshathry (DMU) - Building a Decision Support System to integrate digital evidence with interview investigation. Second supervisor. August 2011. First supervisor: Dr Giampaolo Bella (STRL).
  • Dr Sarah Greenfield (DMU) - Type-2 Fuzzy Logic: Circumventing the Defuzzification Bottleneck. First supervisor. Second supervisors: Prof. Robert I. John and Dr Simon Coupland (CCI). May 2012.
  • Tamas Galli (MPhil DMU) - Fuzzy Logic Based Software Product Quality Models by Execution Tracing. First supervisor. Second supervisor: Dr Jenny Carter (CCI). Technical adviser: Helge Janicke (STRL). Mode of study: Part -time distance International PhD Programme (01/03/2011). February 2014.

Externally funded research grants information

  • Awarded Campus de Excelencia GENIL-BioTIC-UGR Research Visit Grant (1 week) by the University of Granada (Spain). Principal Investigator. €1000. Period: February 2014.
  • Awarded Campus de Excelencia GENIL-BioTIC-UGR Research Visit Grant (1 week) by the University of Granada (Spain). Principal Investigator. €1200. Period: June 2012.
  • Awarded University of Granada Research Visit Grant by the Regional Government of Andalucia (Spain). Principal Investigator. €3184. Period: June 2009 - August 2009.
  • Awarded research funding from the EPSRC for a 3 year projet, which extends my previous work investigating the role of fuzzy logic in aggregation and consensus modelling. Towards a Framework for Modelling Variation, EPSRC, UK, Co-investigator. £145K. Period: 2006 - 2009.
  • Awarded a Royal Academy of Engineering grant support towards my research networking visit to Spain. 2009.
  • Awarded 2 Conference Grants (Royal Society and Royal Academy of Engineering) to disseminate my research findings at IPMU 2006 and FUZZ-IEEE 2008.
  • External research collaborator in Spanish Government Research Projects lead by my collaborators.
  • Linguistic Information in Decision Making Analysis Processes. Preference Modelling and Applications. Spanish Department for Education and Culture, Co-investigator. €91K. Period: 01/01/2010 to 31/12/2012.  
  • Project of Excellence: Developing the Fuzzy Linguistic Model and its Use in WEB Applications. Regional Government of Andalucia (Spain), Co-investigator. €187K. Period: 01/01/2009 to 31/12/2013.
  • Decision Models with Uncertainty in Heterogeneous Contexts. Application to Evaluation Processes in On-line Environments. Spanish Department for Education and Culture, Co-investigator. €50K. Period: 01/01/2007 to 31/12/2009.
  • Project of Excellence: Development of WEB Information Access Systems Based on Artificial Intelligence Techniques (SAINFOWEB). Regional Government of Andalucia (Spain), Co-investigator. €50K. Period: 01/01/2005 to 31/12/2008.
  • An Information System for the Quality of Aerial Transportation Based on Artificial Intelligence Techniques and Oriented Towards the Citizen. Spanish Department of Transport, Co-investigator. €96K. Period: 01/01/2005 to 31/12/2008.
  • Flexible Preference Modelling in Decision Making. Applications in online recommender systems (I) and (II). Spanish Department for Education and Culture, Co-investigator. €33K. Period: 01/01/2003 to 31/12/2006.
  • Spanish National Network in Decision Making, Preference Modelling and Aggregation (I) and (II). Spanish Department for Education and Culture, Co-investigator. €30K. Period: 01/01/2004 to 31/12/2006.
  • Similarities Between Physics and Mathematics in Secondary Education. Regional Government of Andalucia (Spain), Principal Investigator. €700. Period: 01/09/2002 to 30/06/2003.

 

Internally funded research project information

  • Awarded DMU Research Scholarship 2013-14 scheme for 3 years starting from October 2013. This scheme provides for funding to cover both fees and stipend equivalent to the RCUK standard rate (£13,770 for 2012-13) to support one research student from UK or EU. (Principal Investigator with Dr David Elizondo and Dr Benjamin Passow - DIGITS).
  • Awarded DMU Research Scholarship 2012-13 scheme for 3 years starting from October 2012.  This scheme provides for funding to cover both fees and stipend equivalent to the RCUK standard rate (£13,770 for 2012-13) to support one research student from UK or EU. (PI with Dr David Elizondo and Dr Benjamin Passow - DIGITS).
  • Awarded DMU Revolving Investment Fund (RIF) for Research for the project DIGITS: De Montfort Interest Group In Transport Systems. Principal Investigator. £10K. Period: January 2012 - July 2012. 
  • Awarded £4K under the Faculty of Computing Sciences and Engineering (DMU) Pump Priming initiative to promote external collaborations at the University of Granada and the University of Jaen in Spain. 2005.

Professional esteem indicators

Associate Editor and Editorial Board

International journals in ISI Web of Knowledge

International journals not in ISI Web of Knowledge

Guest Editor for international journals in ISI

  • "FUZZY APPROACHES IN PREFERENCE MODELLING, DECISION MAKING AND APPLICATIONS" in the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS), Volume 16, Issue 2 Supp. August 2008. F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera (Eds.).
  • "COMPUTING WITH WORDS IN DECISION MAKING" in the International Journal of Fuzzy Optimization and Decision Making Journal, Volume 8, Number 4 / December 2009. F. Herrera, E. Herrera-Viedma, S. Alonso and F. Chiclana (Eds.). 

Research Council Reviewer and External Examiner

UK

  • EPSRC
  • The Royal Society

International

  • The Research Foundation - Flanders (Belgium) (Fonds Wetenschappelijk Onderzoek - Vlaanderen, FWO)
  • The Romanian National Council for Development and Innovation
  • Portuguese Foundation for Science and Technology (FCT)
  • Austrian Science Fund (FWF)
  • Netherlands Organisation for Scientific Research, Division of Social Sciences.

PhD external examiner

  • Univ. Granada (Granada, Spain)
  • Univ. Jaén (Jaén, Spain)
  • Ulster University (Belfast, UK)
  • University of Valladolid (Valladolid, Spain)
  • École Supérieure d'Électricité (SUPÉLEC, Paris, France).

Conference Organisation, Plenary Talks and Invited Lectures

Organised and Chaired special sessions in the following international conferences:  

  • Special Session FZ08: Fuzzy decision-making: Consensus and Missing Preferences in FUZZ-IEEE 2014 - Beijing (China) that will be held as part of the WCCI2014 from 6-11 July 2014.
  • Special Session 04: Fuzzy Preference Modelling, Decision Making and Consensus in the Second International Conference on Information Technology and Quantitative Management (ITQM2014) that will be held in Moscow - Russia from 3-5 June 2014.
  • Focus Session on Consensus and Decision Making Under Uncertainty in the 2013 IFSA World Congress NAFIPS Annual Meeting Edmonton, Canada June 24-28, 2013.
  • Special Session on Fuzzy Preference Modelling, Decision Making and Consensus in first International Conference of Information Technology and Quantitative Management (ITQM 2013), May 16-18, 2013 at Suzhou, China.
  • Special Session on "Fuzzy Approaches in Preference Modelling, Decision Making and Applications" for the IEEE International Conference on Fuzzy Systems (FUZZ_IEEE), London, UK (2007).
  • Special Session on "Soft Decision Making - Theory and Applications" for the IEEE International Conference on Fuzzy Systems (FUZZ_IEEE), Hong-Kong, China (2008).
  • Special Session on "Fuzzy Decision Making Issues: Preference Modelling and Aggregation" for the 8th International FLINS Conference on Computational Intelligence in Decision and Control, Madrid, Spain (2008).
  • Organised Workshop on "Type-2 Fuzzy Logic and the Modelling of Uncertainty" at the AI-2007 Twenty-seventh SGAI International Conference on Artificial Intelligence, Cambridge, UK.
  • Plenary talk at the 2009 EUROFUSE Workshop on Preference Modelling and Decision Analysis.
  • Invited Lectures at the University of Granada, the University of Pamplona, the University of Valladolid, the University of Castilla-La Mancha in Albacete, the University of Jaen (Spain), Ghent University (Belgium) and University of Portsmouth (UK).
  • Programme committee member of more than 50 international conferences.
Francisco-Chiclana