International Conference on Geomatics, Computing, Engineering, and Applied Sciences (ICGCEAS - 26)

This track focuses on the latest advancements in computing methodologies that enhance efficiency and performance across various engineering applications. Contributions that explore novel algorithms, software development, and computational frameworks are particularly encouraged.

This session will delve into cutting-edge data mining techniques that facilitate the extraction of meaningful patterns from large datasets. Papers that showcase practical applications in engineering and the physical sciences are highly sought after.

This track aims to highlight recent developments in data science methodologies that drive innovation in engineering and life sciences. Submissions that demonstrate the integration of machine learning, statistical analysis, and predictive modeling are welcome.

This session will explore recent advancements in theoretical chemistry that contribute to our understanding of molecular systems and chemical processes. Contributions that employ computational techniques to address complex chemical questions are encouraged.

This track focuses on the role of big data analytics in engineering disciplines, emphasizing techniques that enable the processing and analysis of large-scale data. Papers that present case studies or novel approaches to big data challenges are invited.

This session will examine the application of machine learning techniques in the physical sciences, highlighting innovative approaches to data analysis and modeling. Contributions that demonstrate the impact of machine learning on scientific discovery are encouraged.

This track will address the application of computational methods in engineering design processes, focusing on optimization and simulation techniques. Papers that showcase interdisciplinary approaches to engineering challenges are particularly welcome.

This session will explore innovative data visualization techniques that enhance the interpretation of complex scientific datasets. Contributions that demonstrate effective communication of data insights through visual means are encouraged.

This track aims to foster discussions on interdisciplinary approaches in data science that bridge engineering, physical sciences, and life sciences. Papers that highlight collaborative research efforts and cross-domain applications are invited.

This session will focus on emerging trends in computational chemistry, particularly those that leverage advanced computing techniques to solve chemical problems. Contributions that explore novel theoretical frameworks or computational tools are encouraged.

This track will address the ethical considerations and challenges associated with data science practices in engineering and scientific research. Papers that discuss best practices, regulatory frameworks, and case studies are particularly welcome.