International Conference on Quantum Computing and Artificial Intelligence
(ICQCAI-27)

This track focuses on the development and application of quantum algorithms specifically designed for artificial intelligence tasks. Researchers are invited to explore how quantum computing can enhance machine learning and data processing capabilities.

This session will delve into the integration of deep learning techniques within quantum computing frameworks. Participants will discuss the implications and advancements of deep learning models when applied to quantum data.

This track aims to showcase innovative applications of artificial intelligence in quantum systems. Contributions will highlight real-world use cases and the transformative potential of AI in enhancing quantum technologies.

This session will explore the intersection of predictive analytics and quantum computing. Researchers will present methodologies that leverage quantum technologies to improve predictive models and decision-making processes.

This track focuses on the automation of processes through the synergy of AI and quantum computing. Discussions will cover frameworks and strategies that facilitate automated decision-making and operational efficiency.

This session will address the challenges and solutions related to scalable computing in the context of artificial intelligence. Participants will examine architectures and methodologies that support large-scale AI implementations.