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International Conference on Artificial Neural Networks in IT

3rd Oct – 4th Oct 2026 San Francisco, USA Standard / Physical Participation
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SDG Wheel

SDG-Aligned Research Themes

International Conference on Artificial Neural Networks in IT conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 9 - Industry, Innovation and Infrastructure SDG 11 - Sustainable Cities and Communities SDG 12 - Responsible Consumption and Production SDG 13 - Climate Action

This track focuses on the latest advancements in deep learning methodologies and their applications in various IT domains. Researchers are encouraged to present innovative approaches that enhance model performance and efficiency.

This session explores the role of predictive modeling in optimizing IT systems and infrastructure. Contributions that demonstrate the impact of predictive analytics on decision-making processes are highly encouraged.

This track examines the integration of artificial intelligence in enhancing cybersecurity measures. Papers should discuss novel algorithms and frameworks that improve threat detection and response capabilities.

This session highlights the use of data analytics to optimize IT performance and resource management. Submissions should focus on case studies or methodologies that showcase effective data-driven strategies.

This track addresses the challenges and solutions associated with integrating artificial neural networks in cloud computing environments. Researchers are invited to present findings on scalability, efficiency, and performance improvements.

This session investigates the intersection of software development practices and machine learning techniques. Contributions should highlight best practices, tools, and frameworks that facilitate the incorporation of ML into software projects.

This track focuses on the application of computational intelligence techniques in network management. Papers should explore innovative solutions for network optimization, monitoring, and fault detection.

This session examines the relationship between IT governance frameworks and algorithm design. Contributions should discuss how governance principles can influence the development and deployment of algorithms in IT.

This track explores the role of automation in enhancing system reliability within IT infrastructures. Researchers are encouraged to present methodologies that demonstrate improved reliability through automated processes.

This session addresses the challenges of integrating IoT devices within existing IT frameworks and managing the resulting data. Contributions should focus on innovative solutions for data handling, security, and interoperability.

This track investigates various strategies for optimizing performance in IT services. Papers should present empirical studies or theoretical frameworks that contribute to the understanding of performance enhancement in service delivery.

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