Special Sessions
List Of
Special
Sessions
DETAILED DESCRIPTION:
SS1 – Cyber-Physical Systems and Predictive Maintenance for Enhanced Reliability and Availability in Industry 4.0
The development of Industry 4.0 has brought a paradigm change in the industry’s approach to production and maintenance. This new era leverages cutting-edge technologies such as cyber-physical systems (CPS), the Industrial Internet of Things (IIoT) and advanced data analytics to create highly responsive and efficient industrial environments. The focus is on achieving higher levels of system reliability and availability through predictive maintenance and real-time decision making.
Cyber-physical systems (CPS) play a key role in this transformation by integrating computational capabilities with physical processes to enable intelligent monitoring, control and automation of industrial operations. These systems can simulate working conditions in real time, providing valuable insights that improve production efficiency and decision-making. As a result, CPS is becoming a cornerstone in the evolution towards smart factories and intelligent production environments.
Predictive maintenance complements this approach by moving from traditional, reactive maintenance strategies to more proactive ones. By harnessing the power of big data, machine learning and artificial intelligence, predictive maintenance enables early detection of potential equipment failures, preventing costly downtime and extending the life of machinery. This change not only reduces maintenance costs, but also significantly improves overall system reliability and availability. costs, but also significantly improves overall system reliability and availability.
This special session aims to provide a platform for thought leaders, researchers, and industry practitioners to share their latest findings, innovations, and experiences. The session will cover a wide range of topics that are integral to the successful implementation of Industry 4.0 technologies, fostering an environment of collaborative learning and knowledge exchange.
Topics of interest include but are not limited to the following:
- Smart manufacturing and maintenance
- Smart factories and Industrial Internet of Things (IIoT)
- Robotics and mechatronic systems
- Mechatronics systems design
- Mechanical systems design and analysis
- Digital twins
- Multi-Agent Systems (MAS)
- Automation measuring systems and sensors
- Human-Machine Interaction and Machine-to-Machine Communication (M2M)
- Learning control and cognitive computing
- Reliability and risk assessment
- Cybersecurity applications in industrial systems
- Simulation and modeling of production systems
- Artificial intelligence in decision support systems
- Intelligent systems for predictive maintenance
Attendees will benefit from insightful presentations and discussions exploring the latest advances in CPS and predictive maintenance. They will have the opportunity to network with peers, explore innovative solutions and gain a deeper understanding of how these technologies can improve reliability and availability in the context of Industry 4.0. This session will stimulate new ideas, collaborate and advance the industrial sector.
Organizers:
Katarzyna Antosz: Rzeszow University of Technology, PL
katarzyna.antosz@prz.edu.pl
Erika Ottaviano: University of Cassino and Southern Lazio, IT,
ottaviano@unicas.it
Pierluigi Rea: University of Cagliari, IT,
pierluigi.rea@unica.it
Arkadiusz Gola, Lublin University of Technology, Poland,
a.gola@pollub.pl
Alejandro Pereira: University of Vigo Spain, ES,
apereira@uvigo.es
DETAILED DESCRIPTION:
SS2 – Industrial Engineering in Era of Digital Transformation
Nowadays, collaborative engineering approaches, tools and practices are of upmost importance for reaching a sustainable development in the current digitalization era. Thus, the development of Manufacturing, Management, and Maintenance Models, Methods, systems and platforms oriented to a collaborative and sustainable Industry 4.0 (or I4.0 for short) is a challenging outcome. This special session aims at contributing with new insights regarding manufacturing, management and/ or maintenance paradigms (strategies), methods, tools, and practices aligned with the nowadays necessity to create and implement collaborative and sustainable I4.0 manufacturing systems.
Therefore, contributions are encouraged in manufacturing, management and/ or maintenance to reach collaboration and sustainability purposes in I4.0 oriented manufacturing systems. The authors should consider in their original contributions, the clear identification of the collaboration and/or the sustainability and the I4.0 domain, the clear description of the proposed paradigm, method, tool, and/ or practices approached, and its validation in the scope of at least one of the three main domains considered in this special sessions (collaboration, sustainability and industry 4.0) for at least one of the scientific areas underlying this special session (manufacturing, management, and maintenance).
Regarding this structure for the authors’ contributions, are expected new theoretical and practical insights for the stakeholders involved in the I4.0 design, management and/ or implementation of collaborative and/or sustainable manufacturing systems.
Topics of interest include but are not limited to the following:
- Circular economy, economic, environmental, and/ or social sustainability
- Industrial engineering: manufacturing, management and/ or maintenance:
- paradigms: dynamic, integrated, distributed, intelligent, predictive, parallel and real time based management,
- methods,
- tools,
- practices,
- operations,
- critical success factors,
- metatheory,
- organizational change and transformation,
- learning organization,
- Industry 4.0 pillars:
- Cyber Physical Systems,
- Artificial Intelligence,
- Big data analytics,
- Supply chain management,
- Horizontal and vertical integration,
- Cybersecurity,
- New business models,
- Open Design,
- Cloud manufacturing,
- Additive manufacturing,
- Autonomous and Collaborative Robots,
- Simulation and augmented reality.
Organizers:
Justyna Trojanowska, Poznan University of Technology, PL
justyna.trojanowska@put.poznan.pl
Leonilde Varela, University of Minho, PT
leonilde@dps.uminho.pt
Sobowale Ademola Adeniyi, University of Minho, PT
id10361@alunos.uminho.pt
Vijaya Kumar Manupati, NITIE Mumbai, IN
manupativijay@nitie.ac.in
Michał Szaroleta, Łukasiewicz – Poznan Institute of Technology, PL
michal.szaroleta@pit.lukasiwicz.gov.pl
DETAILED DESCRIPTION:
SS3 – Engineering Applications for Medical and Healthcare Devices – ENGCARE 2026
Technologies and applications for medical and healthcare devices are part of the actual human daily life and with an increasing demand. Nowadays, we are able to find them practically everywhere, apart from the healthcare units, as integrated, among others, in our homes, body, mobile devices and vehicles, with the objective of improving our safety, comfort, performance and quality of life.
We invite researchers, academics, and professionals to submit either original research (work in progress or developed) as well as review articles that will contribute to the dissemination of Engineering Applications for Medical and Healthcare Devices.
Topics of interest include but are not limited to the following:
- Medical devices for monitoring, diagnosis, and therapy
- Blockchain in Healthcare Devices
- IoT-enabled Healthcare Devices
- Cybersecurity in Medical Devices
- Sustainable and Eco-friendly Medical Devices
- Human-Machine Interfaces for Healthcare
- Biomedical sensors
- Healthcare sensors
- Mobile healthcare
- Home healthcare
- Wearable healthcare
- In-car healthcare
- Artificial intelligence in medical devices and systems
- Ambient assistive living
- Tele-healthcare
- Serious games for healthcare and medical training
- Medical robotics
- Social robotics
- Inclusive technology
- Medical devices design
- Safety and usability in medical devices
- AR, VR or MR in healthcare and medical devices
- Emerging Technologies in medical devices and systems
Organizers:
Vítor Carvalho, 2Ai-EST,IPCA & Algoritmi RD- Minho University, PT
vcarvalho@ipca.pt
Filomena Soares, Algoritmi RD- Minho University, PT
fsoares@dei.uminho.pt
Demétrio Matos, iD+-IPCA, PT
dmatos@ipca.pt
DETAILED DESCRIPTION:
SS4 – Optimization in Industry 5.0
This special session aims to bring together cutting-edge research on recent advancements in machine learning algorithms, contributed by both academic researchers and industry practitioners. Submissions focusing on real-world applications, particularly those that enhance user experience in engineering and business contexts, are especially welcome.
The session provides an excellent international forum for sharing knowledge on the theoretical developments, methodologies, and practical applications in Machine Learning and its diverse domains. The following topics reflect some of the diversity of applications and research areas.
Topics of interest include but are not limited to the following:
- Artificial neural networks
- Bayesian networks
- Data Mining
- Decision making by machine learning
- Deep neural networks
- Evaluation metrics for intelligent search
- Hybrid learning algorithms
- Integration of machine learning algorithms with other technological systems
- Intelligent virtual environments
- Learning and forecasting problems
- Learning methods and analysis
- Literature review of machine learning algorithms/applications
- Machine learning algorithms/applications
- Reinforcement learning
- Smart industries and cities
- Statistical learning
- Supervised machine learning
- Unsupervised machine learning
Organizers:
Filipe R. Ramos, CEAUL, University of Lisbon, PT
frramos@ciencias.ulisboa.pt
Fernanda A. Ferreira, UNIAG – Polytechnic Institute of Porto, PT
faf@esht.ipp.pt
Maria Teresa Pereira, Polytechnic Institute of Porto, PT
mtp@isep.ipp.pt
Marisa Oliveira, Polytechnic Institute of Porto, PT
mjo@isep.ipp.pt
DETAILED DESCRIPTION:
SS5 – Intelligent mechatronic systems – design, materials, simulation, and dynamical analysis
The special session on “Intelligent mechatronic systems design, materials, simulation, and dynamical analysis” aims to presents some innovative research results in the field of opto-mechatronics, dynamic analysis and simulation for optimization of the mechatronic systems, new materials and technologies used in construction of smart mechatronic systems, autonomous or semi-autonomous mobile mechatronic systems. The session will cover a wide range of topics that are relevant for the successful development of new mechatronic systems used in various fields.
This special session aims to bring together researchers, academics, PhD students and industry professionals to facilitate the exchange of knowledge and experience and to strengthen future collaborations.
We invite researchers, academics, PhD students and professionals to submit original research or review articles for sharing knowledge in the field of smart mechatronic applications.
Topics of interest include but are not limited to the following:
- Mechatronics of autonomous and semi-autonomous mobile systems
- AI and Data Science in mechatronics
- Intelligent motion control systems for smart mechatronics and robotics devices
- Dynamic analysis of mechatronic systems
- Opto-mechatronic systems
- Materials and technologies used in smart mechatronics
- Advanced mechatronic product design and development
- Mechatronic medical devices design
- Mechatronics applications
Organizers:
Bogdan Gramescu, National University of Sciences and Technology Politehnica Bucharest, RO
bogdan.gramescu@upb.ro
Liliana-Laura Badita-Voicu, National Institute of Research and Development in Mechatronics and Measurement Technique – INCDMTM Bucharest, RO
badita_l@yahoo.com
Doina Daniela Cioboata, National Institute of Research and Development in Mechatronics and Measurement Technique – INCDMTM Bucharest, RO
cioboatadoina@yahoo.com
DETAILED DESCRIPTION:
SS6 – Innovations in Control, Automation and Robotics
This special session addresses all aspects of control, automation and robotics related to designing safe, reliable and efficient engineering applications. Researchers and students from academia as well as industry experts are invited to share their latest findings, best practices, experiences and visions related to these important fields of engineering.
Topics of interest include but are not limited to the following:
- Modern Control Approaches;
- Modelling and Simulation for Control;
- Case Studies of Control and Automation;
- Robotics Applications;
- Software Tools for Control Systems Design, Automation and Robotics;
- New Trends in Engineering Education related to Control, Automation and Robotics;
- Networked Control systems;
- Industrial Networks;
- Industrial Communication Protocols;
- Cyber-Physical Systems;
- Internet of Things;
- Industry 4.0;
- Industry 5.0.
Organizers:
Frantisek Gazdoš, Tomas Bata University in Zlín, Faculty of Applied Informatics, CZ
gazdos@utb.cz
Jiří Vojtěšek, Tomas Bata University in Zlín, Faculty of Applied Informatics, CZ
vojtesek@utb.cz
DETAILED DESCRIPTION:
SS7 – Sustainable Development: Digitalization and 3D Information in Manufacturing Systems
This special session focuses on actual aspects of the UN Sustainable Development Strategy as it applies to research, innovation, and technology, especially industry and transport. Particular attention is devoted to the challenges of their digitalization within the concepts of Industry 4.0 and Industry 5.0, without which efforts to achieve the global Sustainable Development Goals cannot be realized.
We invite researchers, PhD students, university students, specialists from design offices and research centers, and industry and transport experts to contribute to this session. Share your latest research, innovation results, and new scientific ideas that are relevant to the critical areas of engineering in sustainable development and digitalization.
Topics of interest include but are not limited to the following:
- Current missions, strategies, and practical challenges for sustainable industrial and transport development;
- Modeling, IT technologies, and digital methods for representing, processing, and exchanging information in engineering;
- Technologies for optimizing the life cycle of complexes, systems, and products in industry and transport;
- Scientific and technical solutions to the problems of ecologization, decarbonization, green energy, and alternative energy sources;
- The role of 3D information in sustainable development;
- Digital twins;
- Augmented and virtual reality;
- Internet of Things;
Organizers:
Andrii Marchenko, National Technical University ‘Kharkiv Polytechnic Institute’, Kharkiv, UA
andrii.marchenko@khpi.edu.ua
Sergey Dobrotvorskiy, National Technical University ‘Kharkiv Polytechnic Institute’, Kharkiv, UA
sergiy.dobrotvorskyy@khpi.edu.ua
Yevheniia Basova, National Technical University ‘Kharkiv Polytechnic Institute’, Kharkiv, UA
yevheniia.basova@khpi.edu.ua
DETAILED DESCRIPTION:
SS8 – Young Scientists summit on Science and Engineering
Young minds have the power to bring new perspectives and an ability to tackle problems free from conventional solutions, although lacking experience. In this event, young scientists are invited to present their research in science and engineering, with a focus on innovative solutions for a sustainable future. Researchers and students from academia as well as industry are invited to share their latest findings, best practices, experiences and visions related to important fields of science and engineering. Participation in this session provides a well-established platform for undergraduate, MSc and PhD students, postdocs, entrant engineers and other young scientists, contributing to develop presentation skills, build valuable contacts and forge durable scientific relationships.
This session covers a broad spectrum of topics, fostering multidisciplinary discussions and offering excellent opportunities for the exchange of innovative ideas and potential collaborations. Topics include, but are not limited, to energy, environment, and physico-chemical sciences and engineering.
Organizers:
Victor G. L. Souza, METRICS, NOVA School of Science and Technology, Universidade NOVA de Lisboa, PT
v.souza@fct.unl.pt
Ana Luisa Fernando, METRICS, NOVA School of Science and Technology, Universidade NOVA de Lisboa, PT
ala@fct.unl.pt
DETAILED DESCRIPTION:
SS9 – Statistical and Critical Thinking for Responsible and Resilient Decision Making under Uncertainty
In light of UNESCO’s continued highlight on engineering’s crucial role in sustainable development and addressing global challenges, the need to equip professionals and students with advanced decision-making capabilities becomes increasingly urgent. As digitalization, artificial intelligence (AI) and data science transform industry and society, a renewed focus on statistical thinking, critical reasoning, and ethical awareness is vital to navigate the complexity and uncertainty of modern systems.
Building upon the success of previous editions, this special session for 2026 aims to deepen the discussion by embracing new paradigms such as generative AI, trustworthy automated decision-making, resilience in complex systems, and explainable models, while maintaining a strong emphasis on education, methodological rigor, and societal impact.
This special session seeks to gather a diverse community of researchers, educators, and professionals from academia and industry to: share case studies and research exploring integration of statistical and critical thinking in AI-enhanced decision systems; examine how digital technologies (e.g., digital twins, big data analytics) benefit from robust uncertainty quantification; discuss interdisciplinary strategies to develop future-ready engineers and data scientists; reflect on the societal implications, including transparency, fairness, and accountability in data-driven decision-making.
Topics of interest include, but are not limited to:
- Hybrid Human-AI Decision-Making Frameworks
- Generative AI and Ethical Decision Support
- Trustworthy AI and Statistical Transparency
- Teaching Uncertainty and Critical Thinking with Active Learning
- Digital Twins and Statistical Monitoring in Industry 4.0/5.0
- Simulation and Probabilistic Reasoning for Resilient Systems
- Visual Analytics and Interpretability of ML Models
- Educational Innovations for Statistical Literacy in STEM
- AI-Augmented Assessment of Human Judgment and Bias
- Interdisciplinary Methodologies for Sustainable Innovation
- Statistical Methods for Uncertainty Quantification in Industry
- Impact of Temporal and Spatial Statistics on Environmental Engineering
This session will provide a platform for academia and industry to exchange knowledge, explore new approaches, and discuss emerging challenges and opportunities related to the use of statistics, machine learning, and critical thinking in decision-making under uncertainty. We aim to foster collaboration that bridges the gap between educational methodologies and industry needs in this fast-evolving landscape.
Organizers:
Manuela Gonçalves – Centre of Mathematics (CMAT), School of Sciences, University of Minho, PT
Celina Pinto Leão – Centro ALGORITM, School of Engineering, University of Minho, PT
Teresa Malheiro – Centre of Mathematics (CMAT), School of Sciences, University of Minho, PT
DETAILED DESCRIPTION:
SS10 – Robotics, AI, and Digital Twin for Smart Intralogistics
The convergence of Robotics, Artificial Intelligence (AI), and Digital Twin technologies is reshaping intralogistics, enabling smarter, more adaptive, and highly efficient internal logistics systems. This special session will explore the transformative impact of these technologies in optimizing operations, enhancing human-machine collaboration, and enabling data-driven decision-making across industrial environments.
Robotics accelerates automation in tasks such as material handling and inventory control, while collaborative robots enhance flexibility and workplace safety. AI contributes with real-time analytics, demand forecasting, and autonomous decision support. Meanwhile, Digital Twin technology provides a powerful tool for real-time simulation, predictive maintenance, and operational insight through virtual representations of physical systems.
By convening researchers, industry professionals, and technology developers, this session seeks to advance discussions on innovative applications, integration challenges, and future research directions in smart intralogistics. Emphasis will be placed on bridging the gap between academic innovation and industrial deployment.
Topics of interest include, but are not limited to, the following:
• Autonomous and intelligent material handling
• AI-based decision support systems
• Human-robot collaboration and productivity
• Digital Twin for monitoring and optimization
• System integration and interoperability
• Predictive maintenance and quality control
• Implementation challenges and adoption barriers
• Future trends in Robotics, AI, and Digital Twin
• Simulation-based planning and optimization
Organizers:
Pedro Senna pedro.senna@inesctec.pt
António Almeida antonio.h.almeida@inesctec.pt
Ana Correia Simões ana.c.simoes@inesctec.pt
INESC TEC, Campus da FEUP, Rua Dr. Roberto Frias, 4200-465 Porto
DETAILED DESCRIPTION:
SS11 – When Innovation Meets Ethics in Engineering Education
As the demands on engineers evolve in response to complex global challenges—sustainability, digitalization, equity and social responsibility—the intersection of innovation and ethics has become a vital frontier in engineering education.
This special session invites educators, researchers, and practitioners to reflect on how ethical reasoning and innovative thinking can be co-developed through pedagogical strategies, curricular integration, interdisciplinary collaboration, and institutional culture.
We will explore questions such as:
- How can engineering programs prepare students to navigate ethical dilemmas in innovation-driven environments?
- What frameworks and tools (quantitative, qualitative, or digital) support ethical learning outcomes?
- How do we assess students’ ethical awareness, beyond compliance with academic integrity?
- Can innovation in teaching itself become a means of fostering ethical sensitivity?
- How does the incorporation of immersive technologies (e.g., VR/AR simulations) into engineering curricula affect students’ critical thinking and decision-making complexity, compared to traditional case-based learning?
Emerging approaches such as immersive simulations introduce a new dimension to ethical education, where students not only analyze what they would do but experience what they feel and how they react in complex contexts. These technologies, when integrated with tools like eye tracking or heart rate monitoring, generate real-time emotional and cognitive data. Such data, in turn, can feed adaptive AI systems that personalize ethical learning experiences—raising novel ethical questions about the use of biofeedback, privacy, and emotional manipulation.
This session will feature a mix of short paper presentations, case-based discussions, and interactive formats (e.g., live polling, reflective activities, or role-play simulations) to foster co-learning across disciplines.
Expected Contributions and Topics Include (but are not limited to):
- Ethical challenges in emerging technologies and responsible innovation
- Integrating ethics into project-based or service-learning experiences
- Data ethics, AI use in education, and academic integrity
- Tools for measuring ethical development in engineering students
- Cross-disciplinary teaching between engineering, psychology, bioethics, and social sciences
- Institutional strategies to foster an ethical engineering culture
- Immersive technologies and the emotional dimension of ethical decision-making
- Use of biofeedback and adaptive AI in ethical education environments
Keywords: Engineering Education; Ethics in Engineering; Responsible Innovation; Academic Integrity; Interdisciplinary Pedagogy; Ethical Decision-Making; Curriculum Innovation; AI and Data Ethics
Organizers:
Celina Pinto Leão – Centro ALGORITM, School of Engineering, University of Minho, PT
Anabela C. Alves – Centro ALGORITM, School of Engineering, University of Minho, PT
Ana C. Ferreira – Faculty of Engineering and Technologies, Lusíada University, V.N. Famalicão, PT
Ana Voichița Tebeanu, National University of Science and Technology Politehnica, Bucharest, RO
Petr Valasek, Czech University of Life Sciences (CZU) Prague, CZ
DETAILED DESCRIPTION:
SS12 – Digital and Smart Manufacturing for a Resilient and Human-Centric Industry 5.0
The organizers of this special session invite researchers to submit original research papers, surveys, and case studies that reflect the transition from Industry 4.0 to Industry 5.0. This session aims to bring together novel contributions from researchers and practitioners addressing the latest technologies and developments in key areas of smart manufacturing, including advanced and resilient manufacturing technologies and processes, mechatronic devices, human-centered product design and development, smart and sustainable materials, data and artificial intelligence, cyber-physical systems, predictive maintenance, sustainability and circularity, industrial communication, and IoT/IIoT systems. Submissions are also encouraged on emerging topics such as additive manufacturing and new hybrid processes, advanced robotics, modeling and simulation for smart manufacturing, smart material handling and transportation vehicles, vision-guided robotics, digital twins, machinery health monitoring, and edge, fog, and cloud computing. This session provides a forum for reviewing, disseminating, and identifying critical challenges that drive the industrial digitalization process, fostering the development of sustainable and efficient manufacturing systems, very focus on the integration of collaborative intelligence, advanced product design, mass customization, green innovation, and human-machine collaboration.
Topics of interest include but are not limited to the following:
- Human-Centric Design in Manufacturing Systems;
- Collaborative and Assistive Robotics;
- Advanced Product Design and Development;
- Digital Twins and Simulation in Human-Machine Collaboration;
- Additive Manufacturing and Hybrid Processing;
- Intelligent and Sustainable Materials;
- Mechatronic Sensing, Control, and Smart Actuators;
- Cyber-Physical Systems and Embedded Intelligence;
- Machine Learning, Deep Learning and Big Data in Manufacturing;
- Resilient and Adaptive Supply Chains;
- Predictive Maintenance and Self-Healing Systems;
- Edge, Fog, and Cloud Computing Architectures;
- Industrial Communication Protocols (including 5G/6G);
- Vision-Guided Robotics and Smart Vision Systems;
- IoT and Industrial IoT (IIoT) for Human-Aware Systems;
- Sustainability and Circular Economy in Industrial Systems;
- Green and Energy-Efficient Manufacturing Solutions;
- Human-Machine Interfaces and Augmented Reality;
- Mass Customization and Personalization in Production;
- Modelling and Simulation for Smart Manufacturing;
- Ethics and Governance in AI for Manufacturing;
- Case Studies and Experimental Testbeds for Industry 5.0.
Organizers:
Pedro Torres, Polytechnic University of Castelo Branco, PT
pedrotorres@ipcb.pt
Nuno Fernandes, Polytechnic University of Castelo Branco, PT
nogf@ipcb.pt
Flávia Barbosa, Institute of Science and Innovation in Mechanical Engineering and Industrial Engineering, PT
fbarbosa@inegi.up.pt
DETAILED DESCRIPTION:
SS13 – Artificial Intelligence for Scientific Discoveries (AI4SD)
The meeting is intended for discussions and exchange of ideas among researchers who develop and use methods of artificial intelligence (AI), data science and big data analysis in solving scientific and industrial challenges.
AI for Scientific Discoveries (AI4SD) represents the convergence of artificial intelligence (AI) innovation in scientific research and AI-driven scientific discovery, demonstrating their deep integration, and the establishment of a transformative research paradigm.
High-profile voices in AI research and industry have forecasted that AGI will “cure all diseases” and that due to developments in AI, “scientific progress will likely be much faster than it is today”. While these statements underscore the rapid and exciting developments in the AI for Science community, beneath the headlines lie unresolved questions about where current AI methods genuinely advance scientific discovery and where they still hit hard limits. Through our proposed AI for Science workshop, we will bring together experimentalists, domain scientists, and ML researchers to discuss where this boundary lies. Our workshop will highlight common bottlenecks in developing AI methods across scientific application domains, and delve into solutions that can unlock progress across all of these domains. We welcome submissions from all AI for Science areas, but we concentrate our talks and panel on the reach and limits of AI for scientific discovery.
Topics of interest include but are not limited to the following:
- Machine Learning, including supervised learning, unsupervised learning, semi-supervised learning, self-supervised learning
- Active learning, online learning, transfer learning, continual learning etc.
- Reinforcement learning
- AutoML, Meta-Learning, Planning to Learn
- Representation learning for vision, text, audio, language, and other data modalities
- Knowledge Discovery and Data Mining
- Anomaly and Outlier Detection
- Learning from Complex Data
- Causal Modeling and reasoning
- Neuro-symbolic learning & hybrid AI systems (logic & formal reasoning, etc.)
- Physics-informed machine learning
- Computational equation discovery and Symbolic Regression
- Data and Knowledge Visualization
- Explainable AI and Interpretable Machine Learning
- Human-Machine Interaction for Knowledge Discovery and Management
- AI and High-performance Computing, Grid and Cloud Computing
- Optimisation
- AI Creativity
- Process Discovery and Analysis
- Evaluation of Models and Predictions in Discovery Setting
- Applications of the above techniques in scientific domains, such as Physical sciences, Life sciences, Environmental sciences, Natural and social sciences
- Explainable AI for Science
- Symbolic Regression for Science
- Semantic Technologies for Science
- Foundation Models for Science
- Physics-informed Methods for Science
Organizers:
Olena Hrybiuk: International Scientific and Technical University, Institute for Digitalisation of Education of the NAES of Ukraine, UA
o.gribiuk@istu.edu.ua
Kamil Filipek: Centre for Artificial Intelligence and Computer Modelling, Marii Curie Skłodowska University in Lublin, PL
kamil.filipek@mail.umcs.pl
DETAILED DESCRIPTION:
SS14 – Lean Thinking and Engineering Management for Sustainable Innovation
This Special Session explores the interconnected roles of lean thinking, quality management, and engineering management in sustainable innovation for the engineering sector. Emphasis is placed on approaches that combine efficiency, economic vitality, and quality assurance with robust environmental and societal considerations to generate lasting value. The session will highlight waste reduction tools, environmental compliance, and leadership strategies, focusing on how innovation can be both ethical and environmentally conscious while maintaining high performance standards across sustainability domains.
Topics of interest include but are not limited to the following:
- Lean and circular economy
- Quality management and environmental compliance
- Sustainability indicators and engineering KPIs
- Economic and environmental impacts of green innovation
- Engineering management and sustainability targets
- Green innovation strategies and lean R&D
- Energy efficiency and resource optimization through lean approaches
Organizers:
Dr. Judit T. Kiss, University of Debrecen, Faculty of Engineering, Department of Engineering Management, HU
tkiss@eng.unideb.hu
Dr. Domicián Máté, University of Debrecen, Faculty of Engineering, Department of Engineering Management, HU
Dr. Szabolcs Kiss, University of Debrecen, Faculty of Engineering, Department of Engineering Management, HU
Dr. Andrea Matkó, University of Debrecen, Faculty of Engineering, Department of Engineering Management, HU
DETAILED DESCRIPTION:
SS15 – Intelligent Methods Supporting Manufacturing Systems Efficiency
The session is devoted to the latest research and applications of intelligent methods that enhance the efficiency, adaptability, and sustainability of manufacturing systems. With the growing complexity of production environments and the implementation of Industry 4.0 paradigms, intelligent approaches are becoming essential tools for effective modelling, planning, control, and supervision. The session will cover advances in robotics, production planning and scheduling, and decision support, with particular attention to hybrid systems that combine human expertise with artificial intelligence. Risk assessment methods and data-driven techniques such as machine learning, fuzzy approaches, and data mining will also be discussed in the context of improving system resilience and performance. Contributions presenting case studies and industrial applications are particularly encouraged, providing insight into how intelligent methods can translate into measurable improvements in manufacturing practice. The session aims to create a platform for exchanging knowledge, sharing experiences, and stimulating discussion on innovative solutions for the future of manufacturing systems.
Topics of interest include but are not limited to the following:
- Intelligent Methods in Modelling and Design
- Intelligent Methods in Robotics
- Intelligence Methods in Production Planning and Scheduling
- Intelligent Methods in Control and Supervision
- Risk assessment in production systems
- Applications of Intelligent Methods and Systems in Production
- Hybrid intelligence systems
- Machine Learning
- Fuzzy approaches
- Data Mining
Organizers:
Anna Burduk, Wroclaw University of Science and Technology, PL
anna.burduk@pwr.edu.pl
Damian Krenczyk, Silesian University of Technology, PL
damian.krenczyk@polsl.pl
Kamil Krot, Wroclaw University of Science and Technology, PL
kamil.krot@pwr.edu.pl
Kamil Musiał, Wroclaw University of Science and Technology, PL
kamil.musial@pwr.edu.pl
DETAILED DESCRIPTION:
SS16 – Innovation in Engineering to Prevent Failure of Mechanical Components and Structures
This important session will be an opportunity for scientists and engineers from academia and industries around the world to share their scientific findings on all topics relating to innovation in engineering to prevent the failure of mechanical components and structures. This multidisciplinary session will cover many aspects of Mechanical Fracture and Maintenance Management. It will provide rapid, high-quality synergies and communications with engineers and scientists in different areas of Mechanical and Civil Design, Condition-based Maintenance, Materials, Reliability, Risk Analysis, and Artificial Intelligence.
Topics of interest include but are not limited to the following:
- Failure Analysis
- Condition-based-Maintenance
- Fracture Analysis
- Developments of Mechanical Fracture in Advanced Materials
- Life Cycle Assessment
- Extended Life Models
- Fatigue Life Prediction Models
- Risk Management applied to Mechanical Design
- Risk Management applied to Maintenance
- Integrated Management Systems
- Artificial Intelligence applied to prevent failures
- Artificial Intelligence applied to Maintenance Management
- Optimization Models
- Case of studies of naval, aeronautic, aerospatial, automotive, railway and other industrial sectors
Organizers:
Teresa Leonor Martins Morgado, Unit for Innovation and Research in Engineering, Lisbon School of Engineering of Polytechnic University of Lisbon, PT
tmorgado@dem.isel.ipl.pt; tlrcmm@gmail.com
Suzana Paula Lampreia, Naval Research Centre, Science and Technology Department of Portuguese Naval Academy, Escola Naval, Base Naval de Lisboa, PT
suzana.paula.lampreia@marinha.pt; suzanalampreia@gmail.com
António Mário Pereira, – Centre for Rapid and Sustainable Product Development & School of Technology and Management of Polytechnic University of Leiria, PT
mario.pereira@ipleiria.pt