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DII26 — International Conference on Data-Driven Innovation in the Industry
03. Jun 2026 - 07. Jun 2026 • Aveiro, Portugal
Veranstalter:
Portugal, University of Aveiro, Department of Mathematics
Zusammenfassung:
As industries accelerate through digital transformation, the interplay of theoretical rigor, artificial intelligence, and human-centered design is opening new pathways to productivity, resilience, and sustainable innovation. The International Conference on Data-Driven Innovation in the Industry (DII26) provides a multidisciplinary forum for researchers, practitioners, and technologists to present and discuss advances in industrial systems and their socio-technical impact through data-driven approaches. DII26 embraces challenges and opportunities across the primary sector (extraction and harvesting of natural resources), the secondary sector (manufacturing and construction), and the tertiary sector (services that enable production, distribution, and societal well-being). The scientific program spans new data-driven methods, machine learning and general AI for industrial innovation, data engineering and infrastructure, decision support and automation, and human-centric design, alongside ethics, policy, and broader socio-technical implications. The conference further highlights cross-disciplinary methods and emerging technologies, with dedicated space for products and solutions for logistics and manufacturing, as well as student prototypes and work-in-progress. By connecting foundational ideas with deployable systems, DII26 aims to catalyze collaboration and accelerate impactful, responsible innovation across industry.
Kontakt:
DII26 Organizing Committee;     Email: event_dii26@spm.pt
Themen:
Optimization, Operations research, System dynamics & simulation modeling, Machine learning, Deep learning, Predictive maintenance, Computer vision in manufacturing, Industrial IoT (IIoT), Big data pipelines, Edge computing, Decision support systems (DSS), Digital twins, Human-in-the-loop & UX design, Data ethics (privacy/bias/compliance)
Eintrags-ID:
1698643


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Stand vom 1. März 2026