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DEOTIA 2026 : International Conference on Differential Equations, Optimization Techniques, and their Industrial Applications

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Link: https://eventos-spm.pt/event/1/
 
When Jun 3, 2026 - Jun 7, 2026
Where Aveiro, Portugal
Abstract Registration Due May 30, 2026
Submission Deadline Apr 21, 2026
Notification Due May 5, 2026
Final Version Due Jun 3, 2026
Categories    mathematical foundations   computational methods   numerical methods
 

Call For Papers

The University of Aveiro, with the support of the projects ILLIANCE and NEXUS, and the Portuguese Mathematical Society (SPM), is pleased to organize DEOTIA26, to be held from 3–7 June 2026 in Aveiro, Portugal. We warmly invite you to participate.

In an era driven by complex systems and data-intensive challenges, the synergy between differential equations, optimization techniques, and computational modeling plays a pivotal role in shaping scientific and technological progress. The conference DEOTIA26 serves as a premier forum for mathematicians, engineers, and interdisciplinary researchers to share novel insights, theoretical developments, and practical applications that bridge mathematics with real-world problem-solving. The event highlights the transformative power of analytical and numerical methods across diverse domains, emphasizing innovation, efficiency, and sustainability. We mainly consider three key thematic areas:

Mathematical Foundations: This thematic area explores the theoretical aspects of differential equations, variational principles, and optimization theory. It focuses on analytical methods and the development of new mathematical theoretical directions.

Computational and Numerical Methods: This thematic area centers on algorithmic approaches and computational strategies for solving complex differential and optimization problems. Topics include numerical simulation, machine learning-assisted optimization, and big data computational systems.

Solutions and Interdisciplinary Applications: This thematic area focuses on applying mathematical tools to real-world scenarios in engineering, physics, biology, economics, and environmental sciences with special focus in Logistics and Manufacturing —demonstrating how mathematical modeling drives innovation and decision-making across disciplines.

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