Eureka Business AI 2026

Witold Pedrycz is Professor in the Department of Electrical and Computer Engineering at the University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences in Warsaw, Poland.

Dr. Pedrycz is a foreign member of the Polish Academy of Sciences and a Fellow of the Royal Society of Canada. He has received several awards, including the Norbert Wiener Award from the IEEE Systems, Man, and Cybernetics Society, the IEEE Canada Computer Engineering Medal, the Cajastur Prize for Soft Computing, the Killam Prize, the Fuzzy Pioneer Award from the IEEE Computational Intelligence Society, and the 2019 Meritorious Service Award from the IEEE Systems, Man and Cybernetics Society.

His main research directions involve Computational Intelligence, Granular Computing, and Machine Learning. He serves as Editor-in-Chief of WIREs Data Mining and Knowledge Discovery.

Machine Learning and Artificial Intelligence have produced many success stories, including in high-criticality areas. At the same time, limitations have become visible when ML systems rely exclusively on data and assume that data fully represents the problem to be solved.

The lecture presents Informed Machine Learning as a methodology where data and knowledge are used together to design ML systems. It discusses how data and knowledge operate at different levels of information granularity, and why a holistic knowledge-data development perspective is needed.

The talk offers a taxonomy of Informed ML, connects it with knowledge representation, and discusses neuro-symbolic systems, physics-oriented constructs, and learning-for-reasoning, reasoning-for-learning, and reasoning-learning approaches.

Prof. Dr. Rafael A. Espin-Andrade is an international scientific leader with extensive expertise in Logic, Computational Intelligence, Data Analytics, Business Analytics, Artificial Intelligence, and Game Theory.

He has developed theoretical foundations and practical applications, authored numerous publications, and served as professor and coordinator of graduate programs in Data Analytics, Artificial Intelligence, Machine Learning, and Business Analytics.

His work has been central in advancing Hybrid Augmented Intelligence and Wide Knowledge Discovery as frameworks for integrating human reasoning and artificial intelligence in decision-making systems. His contributions include the development and application of Archimedean Compensatory Fuzzy Logic and related hybrid approaches for interpretability and explainability.

The lecture presents a problem-driven consultancy approach where AI is introduced as a practical and explainable tool for solving high-priority business challenges, especially for SMEs working under constraints of time, resources, and uncertainty.

The methodology is grounded in Hybrid Augmented Intelligence, Human-in-the-Loop collaboration, and Wide Knowledge Discovery. It emphasizes transdisciplinary interpretability supported by frameworks such as Archimedean Compensatory Fuzzy Logic.

Over time, each solved problem contributes to a coherent architecture of knowledge, decision logic, quality management, training, and action. The lecture frames this progression as the emergence of a Cognitive ERP built dynamically through real business problem solving.

Prof. Dr.-Ing. Jorge Marx Gómez is Full Professor and Head of the Chair of Business Information Systems (Very Large Business Applications) at the Carl von Ossietzky University of Oldenburg, Germany.

He is Director of the Center for Environmental and Sustainability Research at Oldenburg University and has held board and leadership roles in sustainability, open source, environmental management information systems, and applied informatics.

His research interests include business information systems, federated ERP systems, software technology, business intelligence, data science, deep learning, interoperability, environmental management information systems, ICT for sustainability, and e- and mobile commerce. He has supervised and reviewed more than 50 doctoral theses and coordinated national and international research and mobility projects.

The lecture explores how ERP systems are evolving in the context of AI, real-time data, and cyber-physical systems.

It discusses the integration of inputs from technologies such as drones and distributed sensing systems into enterprise environments, enabling real-time operational visibility, efficiency, and responsiveness.

The session connects traditional enterprise systems with AI-enabled business environments, focusing on scalability, data integration, operational outcomes, and ERP systems as a backbone for AI-driven transformation.

Jesús María Velásquez-Bermúdez began his career in 1970 as a programmer, working across academic and business fields. He was a researcher and professor at Simón Bolívar University.

In 1978, he founded PDC Ingenieria, and in 1990 he created the OPTEX Optimization Expert System, which evolved into Generative Artificial Intelligence in 2000.

He is Founder and Scientific Director of HYPOTHALAMUS Artificial Intelligence, where he has developed innovations in Decision-Making Artificial Intelligence, including Artificial Brains. He has managed more than 100 international projects and received multiple awards, including the 2024 Artificial Intelligence Award from the Society of Industrial Engineering and Operations Management.

The lecture frames the evolution of modern mathematics and computing across Industry 3.0, Industry 4.0, Industry 5.0, and Industry 6.0.

It argues that Industry 6.0 is changing the mathematical modelling of Artificial Intelligence through orchestration of swarms of cognitive robots and living industrial ecosystems.

The presentation introduces these concepts as emerging terms with roots going back at least 15 years, while positioning them as central to the next industrial era.

Virgil Acuna is an engineer and researcher with a background in Electrical and Aerospace Engineering, specializing in robust autonomy, navigation, and control for unmanned aerial vehicles.

His work focuses on reliable UAV operations within the National Airspace System and emerging airspace concepts in UTM, UAM, and AAM.

He applies these technologies to mission-driven domains including search and rescue, precision agriculture, and autonomous delivery. He also teaches robotics, artificial intelligence, and precision navigation.

The lecture presents a precision agriculture consulting and field intelligence service that helps farms improve irrigation, monitor soil conditions, and manage field variability using ground-based sensing, wireless data collection, and UAV-enabled operations.

UAVs allow faster and more consistent data collection across large field areas and hard-to-reach zones, reducing repeated manual sampling and supporting faster responses to changing conditions.

The service model helps farmers turn field information into practical action through soil moisture monitoring, field variability assessment, irrigation planning, management zone mapping, and targeted recommendations.

Dr. Calixto Vallejo is dedicated to elevating human potential through applied science and disciplined innovation. With more than 35 years of experience, his work spans engineering, strategic leadership, and venture development across technology-driven organizations.

He has guided teams and enterprises in aligning process optimization, manufacturing excellence, and organizational strategy into scalable systems that deliver measurable impact.

His work focuses on translating complex scientific principles into real-world applications that strengthen individuals, communities, and the future of human performance.

The lecture addresses the explainability crisis in healthcare AI, where black-box systems influence clinical decisions without providing logic that clinicians can trace or audit.

It presents Archimedean Compensatory Fuzzy Logic, Hybrid Augmented Intelligence, and Wide Knowledge Discovery as frameworks for explainable, regulatory-aligned AI systems.

The lecture focuses on multi-modal health AI, combining genomic panels, clinical biomarkers, wearable physiological sensors, and patient-reported outcomes into a semantically coherent reasoning framework that supports clinical trust and governance.

Juan Carlos Rodriguez is a scientist, strategist, and entrepreneur working across biotechnology, artificial intelligence, and precision health innovation.

As Co-Founder and CEO of Culminate H Labs since January 2016, he has positioned the organization within the longevity revolution, connecting genomics, AI-driven epigenetic interventions, and cellular optimization.

His expertise spans optimization as a service, decision analytics, IP monetization, growth capital strategy, sustainable innovation, deep neural networks, behavioral science, regenerative agriculture, sensor hybridization, artificial intelligence, and immersive experiential learning.

The lecture addresses AI explainability in food security and vertical farming, connecting transparent reasoning systems with community-based food systems.

It presents Hybrid Augmented Intelligence and Cognitive Model Embedment as mechanisms for incorporating community voices and cultural food preferences into AI recommendations.

The session demonstrates how ACFL-based food systems AI can support transparency, automation with human agency, and data-driven precision grounded in community knowledge and equity.