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International Conference on Artificial Intelligence and Materials Science

ICAIMS

29th Sep – 30th Sep 2026 Edirne, Turkey

Official Invitation Letter Available

An official invitation letter will be provided upon successful registration for your participation in the conference.

Benefits of Registering as Listener

Access to All Conference Sessions

Plenary, keynote and parallel sessions

Networking Opportunities

Connect with global educators & researchers

Certificate of Participation

Digital certificate of participation

Invitation Letter Support

Official invitation letter after successful registration

Conference Kit / Digital Materials

E-proceedings & resource materials

Access to Keynote Sessions

Learn from leading experts & scholars

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Standard Registration Closed
The deadline for Standard Participation has ended. Participants may continue with Virtual Registration to join the conference remotely.
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Terms & Condition

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Conference Session Tracks

UN SDG Wheel

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

SDG 7 SDG 9 SDG 12
01 Artificial Intelligence in Materials Discovery +
This track focuses on the application of artificial intelligence techniques in the discovery of new materials. It will explore innovative methodologies and case studies that demonstrate the potential of AI to revolutionize materials science.
SDG 9 SDG 12
02 Machine Learning Techniques for Material Property Prediction +
This session will delve into various machine learning approaches used to predict material properties. Emphasis will be placed on the accuracy and efficiency of these predictive models in practical applications.
SDG 9 SDG 12
03 Data Mining Approaches in Engineering Materials +
This track will examine data mining techniques applied to engineering materials, highlighting their role in extracting valuable insights from large datasets. Participants will discuss challenges and solutions in implementing these approaches.
SDG 9 SDG 12
04 Integrating Experimental Techniques with AI +
This session will explore the integration of experimental methodologies with artificial intelligence techniques in materials science. The focus will be on how this synergy can enhance the understanding and development of advanced materials.
SDG 9 SDG 12
05 Physics-Based Constraints in AI Applications +
This track will investigate the incorporation of physics-based constraints in artificial intelligence applications within materials science. Discussions will center around how these constraints can improve model reliability and predictive capabilities.
SDG 9 SDG 12
06 Machine Learning in Nanotechnology and Smart Materials +
This session will highlight the role of machine learning in advancing nanotechnology and smart materials. Participants will share insights on how AI can facilitate the design and optimization of these innovative materials.
SDG 9 SDG 12
07 Challenges in Applying AI to Materials Science +
This track will address the various challenges faced when applying artificial intelligence techniques in materials science. Participants will engage in discussions on overcoming these obstacles to enhance research outcomes.
SDG 9 SDG 12
08 Theory-Guided Machine Learning in Materials Science +
This session will focus on the application of theory-guided machine learning approaches in the field of materials science. Emphasis will be placed on how theoretical insights can inform and improve machine learning models.
SDG 9 SDG 12
09 Machine Learning Methods in Materials Informatics +
This track will explore the use of machine learning methods in materials informatics, emphasizing their role in data-driven decision making. Participants will discuss the latest advancements and applications in this rapidly evolving field.
SDG 9 SDG 12
10 Computational Materials Science and AI Integration +
This session will examine the integration of computational materials science with artificial intelligence techniques. The focus will be on how this combination can accelerate materials research and development.
SDG 9 SDG 12
11 Machine Learning for Energy Materials +
This track will investigate the application of machine learning techniques in the discovery and optimization of energy materials. Participants will discuss innovative approaches to enhance energy efficiency and sustainability through AI.
SDG 7 SDG 9