The International Virtual Workshop on Business Analytics, Eureka 2021

Held on June 2 to 4, 2021, by UACJ

The objective of the meeting is to share Hybridization and Transdisciplinary science works and their application in Knowledge Discovery, Knowledge Engineering and Management, as well as Decision Making and Optimization. The dialogue regarding the exploration of synergies among the participants, which could be expressed in joint papers and projects, and the impact on the city and region where the meeting is organized are the most important objectives as it is the tradition of the Eureka’s congresses. Eurekas Community is characterized by the diversity and openness of the Computational Intelligence and Operations Research scientific communities, as well as General and Theoretical Hybridization as two of their more critical scientific strategies; these Virtual Meeting sessions are sure to be very important —as it is usual in Eureka— as an initiative towards interdisciplinary and transdisciplinary science by synergies of the participants.


Design and Analysis of Information Granules and Rule-based Architectures with Federated Learning

In data analytics, system modeling, and decision-making models, the aspects of interpretability and explainability are of paramount relevance, just to refer here to explainable Artificial Intelligence (XAI). They are especially timely in light of the increasing complexity of systems one has to cope with and ultimate concerns about privacy and security of data and models. With the omnipresence of mobile devices, distributed data, and security and privacy restrictions, federated learning becomes a suitable and practically viable alternative.


Information granules are building blocks forming the interpretable environment capturing the essence of data and key relationships existing there. Their emergence is supported by a systematic and focused analysis of data. At the same time, their initialization is specified by stakeholders or/and the owners and users of data.  We cover a comprehensive discussion of information granules-oriented design of information granules by engaging an innovative mechanism of federated unsupervised learning in which information granules are constructed and refined with the use of collaborate schemes of clustering. The development of fuzzy rule-based models engaging federated learning is also discussed.

Speaker: Prof. Dr. Witold Pedrycz

University of Alberta, Canada

Witold Pedrycz (IEEE Life Fellow) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. In 2009, Dr. Pedrycz was elected a foreign member of the Polish Academy of Sciences. In 2012 he was elected a Fellow of the Royal Society of Canada. In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. He is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society, and 2019 Meritorious Service Award from the IEEE Systems Man and Cybernetics Society.  His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks among others.

Dr. Pedrycz is also vigorously involved in editorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Co-editor-in-Chief of Int. J. of Granular Computing (Springer) and J. of Data Information and Management (Springer).  He serves on an Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of international journals. 

Towards a new Augmented Analytic based on Fuzzy Predicates: The transformation of Computational Intelligence towards it. The history and role of the Eurekas Community

This presentation gives some details about a review and analysis paper that offers a transdisciplinary, methodological, and strategic vision for soft computing development towards a wider favorable impact in data analytics.  Strategies are defined, explained, and illustrated by examples. The paper and the presentation also show how these strategies are expressed in three dimensions of an ambitious Eurekas Community actions plan in course. They are all integrated into a master strategy called wide knowledge discovery, which offers a way towards the augmented analytics paradigm. Some contributions of this work are defining what kind of mathematical elements should be introduced into soft computing towards a better impact on the area of data analytics, offering orientation towards building new mathematical elements, and defining why and how they can be introduced. The paper is part of the Special Issue: Soft computing: Theories and applications II.

Speaker: Prof. Dr. Rafael Alejandro Espin-Andrade

Autonomous University of Coahuila, Mexico

Professor Dr. Rafael Alejandro Espin-Andrade is Full Professor of the Institute of Multidisciplinary Research for Innovation Management and Entrepreneurial Development (IMIGIDE) of the Accounting and Administration Faculty of the Autonomous University of Coahuila, Mexico, Co-president of Eurekas Community, Coordinator of the Iberian American Network of Knowledge Discovery Eureka Iberoamerica, and Executive secretary of the Coordination Board of the Transdisciplinary Science Network Eureka International. He is a Mexican National Researcher of level II (SNI II). He has published numerous papers and participated as lecturer in multiple congresses and international academic programs of America and Europe, in the areas of Mathematical Fuzzy Logic, Knowledge Discovery, Decision Making, Cooperative Games Theory, Management Sciences, Business Analytics and Business Intelligence. He has leaded binational and multilateral scientific and academic projects and has been chair of several international scientific congresses, workshops, and clusters of sessions. 

Computing with Words in Decision Making: Its Application to Climate Policy

The concept of computing usually implies calculation processes either by mathematical means of numbers and symbols or by a computer. Paying attention to computing processes done by human beings, it is remarkable that they employ mostly words in computing and reasoning, arriving at results linguistically expressed from linguistic premises. Hence, Computing with Words (CW) applies the same view to their computing processes aiming at obtaining linguistic outcomes from linguistic inputs. Because words have fuzzy denotations when they are used by human beings, the paradigm of Computing with Words was clearly stated as a branch of fuzzy logic.

The complexity of decision-making problems implies uncertainty that on many occasions has been modelled by means of linguistic information, mainly based on fuzzy-based linguistic approaches. Several of these approaches have been successfully applied in decision-making to address challenges and resolve problems associated with environmental, energy, and climate policy. Therefore, it is important to point out the trends in CW and its application for climate policy for supporting policy makers together with the challenges ahead.

Speaker: Prof. Dr. Luis Martínez
University of Jaen, Spain

Luis Martínez is currently a Full Professor with the Computer Science Department, University of Jaén, Jaén, Spain. He is also Visiting Professor in University of Technology Sydney, University of Portsmouth, and in the Wuhan University of Technology.  He has been main researcher in 16 R&D projects, also has published more than 150 papers SCI indexed and more than 200 contributions in Inter/national Conferences related to his areas. His current research interests include decision making, fuzzy logic-based systems, computing with words and recommender systems. He was a recipient of the IEEE Transactions on Fuzzy Systems Outstanding Paper Award 2008 and 2012. He is a Co-Editor-in-Chief of the International Journal of Computational Intelligence Systems and Associate Editor of the journals, including the IEEE Transactions on Fuzzy Systems, Knowledge Based Systems, Information Fusion. Eventually, he has been appointed as Highly Cited Researcher 2017-2020 in Computer sciences.

Implication of Machine Learning on Data Management in Companies

Speaker: Prof. Dr. Jorge Marx Gómez

University of Oldenburg, Germany

Prof. Dr. Jorge Marx Gómez studied Computer Engineering and Industrial Engineering at the University of Applied Science in Berlin (Germany). He was a lecturer and researcher at the Otto-von-Guericke-University Magdeburg (Germany) where he also obtained a PhD degree 2001 in Business Information Systems. From 2002 until 2003 he was a visiting professor for Business Informatics at the Technical University of Clausthal (Germany) and worked as guest lecturer in different countries. In 2004 he received his postdoctoral lecture qualification (Habilitation) at the Otto-von-Guericke-University Magdeburg.

In 2004 he received a Honorary Professorship in Business Informatics at Universidad Central de las Villas (Cuba). Since 2006 Jorge Marx Gómez is a full professor and chair of Business Information Systems at the Carl von Ossietzky University of Oldenburg (Germany). He is furthermore the director of the Center for Environmental and Sustainability Research (COAST) at Oldenburg University and board member of the Energy

Group at OFFIS-Institute. His research interests include Business Information Systems, Federated ERP-Systems, Business Intelligence, Data Science, Applied AI, Interoperability, Environmental Management Information Systems, ICT for Sustainability and E- and Mobile-Commerce. Prof. Dr. Jorge Marx Gómez successfully coordinated several national and international research, capacity building and mobility projects (Tempus, Erasmus Mundus, DAAD) and participated in several EU-FP7 projects.

Emergent and Evolvable Ports: How this concept might be for Latin American Ports

The port model prevailing in Latin America (LATAM) is the result of the major reforms of the decades of the 1990s and 2000s. It allowed for substantial achievements as regards the reduction of foreign trade port costs. Changes in the economy may have been influenced by improvements in port performance and operations; though the improvement in seaport management and technology in LATAM has not been quite as impressive as in other regions around the world. The economic environment in which ports operate daily generate expectations that must address not only the creation of better infrastructure and technology but also its adaptability to challenges in the global environmental landscape. Port authorities in the Port LATAM region must re-define appropriate strategies to specify relevant core businesses and competencies to position ports for sustainability. Built on competitive grounds and thus finding the proper context/conditions opportunities for cooperation, collaboration and coordination among ports will emerge into the development for long-term future success. However, shortcomings in reliable data and information exchange often hamper collaborations and partnerships among the initiatives. The challenge goes beyond information technologies because intelligent business processes must be embedded in suitable solutions as the key factor for port competitive advantage. The set of integrated tools supporting businesses and IT users in managing process execution is known as Business Process Intelligence (BPI). The use of computational intelligence tools and methods involving knowledge discovery and computer-aided strategic decision-making are also relatively new endeavours in the port domain.

Speaker: Dr. Ana X. Halabi Echeverry

NextPort, Colombia

Ana X. HALABI-ECHEVERRY is a researcher and data scientist currently focused on inter-port systems and adaptive, flexible and evolvable systems. She is Doctor of Philosophy in Computer Science from Macquarie University, Australia. Master’s Degree in Hydrosystems from Pontifical Xavierian University, Colombia. Specialist in Organisational and Administrative Control Systems from Los Andes University Colombia. Industrial Engineer from Pontifical Xavierian University, Colombia. Associate of NextPort vCoE, a Scientific Association newly created to overcome research gaps that, in an ethical and sustainable way, addresses port data governance and management challenges in Latin America. It is expected that port-related communities increase in intelligence (also data transfer) for collaborative planning. Dr. HALABI-ECHEVERY is convinced of the several opportunities that seaports have in Latin America. Fifteen years of experience in academic and leadership positions within academia. 

Dr. HALABI-ECHEVERRY has international recognition for her achievements in the target sector, publishing in academic peer-review journals such as Springer Special Editions, Taylor and Francis, Elsevier and IEEE Publications. She currently serves as a reviewer of Informs Journal on Applied Analytics.

 Local experiences applying Artificial Intelligence in Bioengineering: Myths and Reality

Undoubtedly, Artificial Intelligence (AI) takes on more and more prominence in processing data coming from practically all fields, to make them useful in decision support. But what do we exactly mean when we say "Artificial Intelligence"? Are the solutions suggested by AI available to anyone? When do we say that a system is "smart"? How “smart” are AI-based systems? What do we expect from AI in the near future? How do we evaluate if an “intelligent” system is robust and capable of generalizing what it has learned? Can AI generate fake biomedical Information? Progress is so overwhelming that it requires us to be aware of new ideas and approaches all the time. In addition, it demands powerful hardware, which becomes a limitation in many cases. In this talk, these questions and challenges are addressed, taking as a starting point some applications of AI methods in a bioengineering laboratory dedicated to the acquisition and processing of signals, medical images, and biomedical data in general. 

Speaker: Prof. Dr. Gustavo Javier Meschino
University of Mar del Plata, Argentina

Gustavo Javier Meschino. Electronic Engineer (1997). Doctor of Engineering, Electronic Orientation (2008). Titles awarded by the National University of Mar del Plata. Associate Professor with Exclusive dedication. Researcher Category II of the Secretariat of University Policies, granted since 2014 (there are V categories, I is the highest). Director of the Bioengineering Laboratory of the Institute for Scientific and Technological Research in Electronics (ICYTE - Universidad Nacional de Mar del Plata - CONICET). Director of the Doctorate in Engineering, Electronic Orientation. Member of the Steering Committee of the Argentine Society of Bioengineering (SABI). Undergraduate and graduate teacher in Electronic Engineering and Artificial Intelligence. He has directed degree projects in these areas, as well as doctoral students and postdoctoral researchers.

His research areas include Artificial Intelligence techniques (Machine Learning, Computational Intelligence) applied to biomedical image and signal processing, in conjunction with the coordination of design projects for biomedical signal acquisition and processing devices.

Artificial Hypothalamus: Artificial Intelligence and Mathematical Programming Integration

Today when we closely examine the supply and demand chain process of any industrial sector we find significant operational latency with poor visibility and the inability to fulfill demand resulting in lost revenue. To overcome these inefficiencies, we need to focus on the core fundamentals of the enterprise. At the nucleus of the enterprise, what we like to call the hypothalamus, it is extremely necessary to have ample knowledge and visibility of the entire chain process. A meticulous composition and relationship between raw materials, services, products, and customer-centric demands. This conference focuses on what is the hypothalamus of an enterprise and how is it built. Like the human hypothalamus key functions and drivers are universal. Yet each hypothalamus is different. They vary in acquiring knowledge through experience where some of us have more knowledge due to experience than others. Or in the case of an enterprise the acquisition and processing of information enables the discernibility of sharp insight that delivers impactful decisions when you most need them. The hypothalamus while bespoke to each enterprise and its business model needs to have a coherent information system. A tactical design throughout its entire process in order ensure it sees supplies and demands with the assurance to fulfill them and leverages the opportunity. The essential elements of this design must occupy a robust framework of algorithms comprised of artificial cognitive agents that model the world and solve problem like neurons in the brain. A carefully structured series of intelligent and autonomous algorithms establish a holistic view of a problem, self-learn, and solve it by using high-complexity mathematical modeling. The artificial hypothalamus supersedes a neural network made up of point-neurons. It is a dynamic and self-organizing sparse network culminated by the integration of multi-function cognitive agents operating simultaneously in real-time like the human hypothalamus. Envision a future not so distant where autonomous algorithms can plan and operate a manufacturing facility, seamlessly run smart cities, optimize net zero transportation fleets, or automate hospitals for better care. All to elevate quality of life while preserving the balance of nature. As our global population grows exponentially the supply chain relationship has become disproportional to demand. The need to incorporate an artificial hypothalamus goes beyond fulfilling demand, our survival and sustainability depends on it.

Speaker: Ph.D. Jesus M. Velásquez-Bermúdez
DecisionWare, Colombia

Doctor in Engineering of the Mines Faculty of the Universidad Nacional de Colombia (2006). Industrial Engineer and Magister Scientiorum of the Universidad Los Andes (Colombia, 1975). Postgraduate studies in Planning and Engineering of Water Resources (Simon Bolivar University, Caracas) and in Economics (Los Andes University). Chair of CLAIO 2008. Consulting engineer with experience in management of projects in mathematical modeling, industrial automation, and information systems, for large companies in multiples countries. Nine years of experience as a University Professor (Universidad Simón Bolivar (Caracas), Universidad de Los Andes (Bogotá), Universidad de La Sabana (Bogotá), Universidad Nacional de Colombia (Medellin)). 

LOGYCA Award for Innovation and Logistic Excellence 2006 (GS1-Colombia). ACOLOG Award to the Investigation in Logistic (2006). Prize ACIEM-ENERCOL Award to Colombian Engineering (1998). ALBERTO LEON BETANCOURT Operations Research Award (1986). President of the Colombian Society of Operations Research (2000-2008). Vice-president of the Latin-Ibero American Association of Operations Research (2004-2008). Member by Colombia Executive Committee of the International Federation of Operations Research Societies (2002).


Consensus Reaching Processes for Large Scale Group Decision Making: Theoretic and Software

Organizers: Rosa Mª Rodríguez Domínguez and Álvaro Labella Romero

University of Jaen, Spain

Consensus reaching processes (CRPs) provide solutions acceptable to all the experts participating in group decision problems, they are demanded in many real-life contexts. Given the variety of existing approaches to support CRPs, this seminar considers three main objectives. Firstly, it revises and introduces a taxonomy that provides an overview and categorization of some existing consensus models for group decision-making problems defined in a fuzzy context, taking into account the main features of each model. Secondly, it discusses the performance of classical CRP models within contexts with a large number of experts, such as e-marketplaces and social networks. Finally, the software AFRYCA that provides support for the CRPs, is introduced to show its features and how to apply different consensus models to deal with group decision-making problems

This seminar will focus on some new requirements to the solution of consensus-based group decision-making problems, such as

Eureka Universe: The Universal Analyst

Organizers: Fernando Padrón, Edgar Pedraza and Carlos Llorente

Tecnológico Nacional de México / Instituto Tecnológico de Cd. Madero, Mexico

Business Analytics (BA) Systems are toolboxes that need user knowledge about algorithms, as well as mathematical and computer sciences theories. On the other hand, Business Intelligence (BI) systems have been evolving towards frameworks which show by diverse sophisticated visualization ways and dashboards, information about the decisión making problem, using specific business analytics techniques. BA and BI systems are not used by decisión makers, such as CEOs and entrepreneurs, the real owners of business ideas and knowledge about them, limiting the effective direct use of those systems in business decision-making real problems.

Eureka-Universe: The Universal Analyst is a unique BA and BI system which allows solving the following independent tasks and mixing them towards Decision Making Problems solutions, without needing any users knowledge about mathematics and computers sciences theories and algorithms; just their own knowledge about the business and common sense for the interaction with a graphical and based on natural language editor.

Eureka-Universe has been possible because of the scientific results of the cooperation into the framework of Eurekas Community, and its networks Eureka Iberoamerica and Eureka International. They have elaborated transdisciplinary theories based on Fuzzy Logic, which allows modeling and interpretation by natural and professional languages for the analysis of metacognitive systems and processes like evaluation, decisión making, reasoning, as well as logical and statistical inferences.

Knowledge Discovery is possible through Eureka-Universe from the Discovery, evaluation, and inference of fuzzy predicates. Eureka-Universe allows the creation of projects starting on a database.


Organizer: J. Patricia Sánchez Solís (mail)

Universidad Autónoma de Ciudad Juárez, México

Scope and Motivation

The International Postgraduate Research Consortium within the Eureka Workshop 2021 aims to provide postgraduate students (master's and doctoral degrees) the opportunity to obtain recognition for the quality of their research, according to the evaluation of expert researchers. Also, the best-evaluated works will receive an invitation to publish their research in one of the special issues of the Workshop. In case of being accepted by the journal, Eurekas Community will cover the article processing charges.

Participation requirements

Those students who submit and present an extended abstract in the Workshop derived from their thesis will be able to participate. Students interested in the consortium should send an email to and with the following complementary information:

Please, check the full Call here.



Journal: Axioms

Indexed in JCR and Scopus


Journal: Journal of Combinatorial Optimization Problems and Informatics (IJCOPI)

Indexed in Emerging Sources Citation (Web of Science), SciELO and CONACYT.


Journal: Polytechnic Open Library International Bulletin of Information Technology and Science (POLIBITS)

Indexed in SciELO, Cabell's Directories, LatIndex, and CONACYT.


Conference Chair


Universidad Autónoma de Cd. Juárez

Program Chair

Dr. Claudia Guadalupe GÓMEZ SANTILLÁN

Tecnológico Nacional de México / Instituto Tecnológico de Cd. Madero

Coordinator of the Eureka's Scientific Advisory Board


Tecnológico Nacional de México / Instituto Tecnológico de Cd. Madero