This track focuses on the latest developments in HPC architectures that enhance computational efficiency and scalability. Participants will explore innovative designs and their implications for big data processing.

This session will delve into the use of predictive analytics to solve complex engineering problems. Emphasis will be placed on methodologies that leverage big data for improved decision-making and forecasting.

This track examines the integration of machine learning algorithms in the analysis of large datasets. Discussions will include the challenges and solutions associated with implementing these techniques in engineering contexts.

This session will explore the intersection of artificial intelligence and high-performance computing systems. Participants will discuss how AI can optimize data processing workflows and enhance system performance.

This track addresses the need for scalable computing solutions to manage and analyze big data effectively. Presentations will highlight innovative strategies and technologies that support scalability in engineering applications.

This session focuses on methodologies for integrating diverse data sources to improve analytics outcomes. Participants will share insights on overcoming integration challenges in engineering domains.