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International Conference on Iterative Methods and Convergence Analysis

📅 13–14 May 2027 📍 California, USA 👤 Standard / Listener

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Conference session tracks

Key research areas covered across the sessions — tap a track to read more.

This track focuses on the latest developments in iterative methods for solving linear and nonlinear equations. Researchers are invited to present novel algorithms and their convergence properties.

This session will explore various techniques for analyzing the convergence of numerical methods. Contributions that provide new insights into convergence rates and conditions are particularly welcome.

This track is dedicated to the study and application of Krylov subspace methods for large-scale problems. Papers discussing theoretical advancements and practical implementations are encouraged.

This session will examine innovative preconditioning techniques that enhance the performance of iterative solvers. Contributions should address both theoretical and computational aspects of preconditioning.

This track aims to discuss the stability of numerical algorithms in various contexts. Researchers are invited to present studies that analyze and improve the stability of existing methods.

This session will focus on fixed point iteration methods, including their theoretical foundations and practical applications. Contributions that highlight new fixed point results or applications in real-world problems are encouraged.

This track addresses numerical methods for solving eigenvalue problems, which are crucial in many scientific and engineering applications. Papers that propose new algorithms or enhance existing techniques are welcome.

This session will explore innovative approaches to solving nonlinear systems of equations. Contributions should focus on both theoretical advancements and practical implementations.

This track is dedicated to the development and application of numerical methods for sparse matrices. Researchers are invited to present new algorithms that exploit sparsity for improved efficiency.

This session will cover the theory and application of multigrid methods for solving partial differential equations. Contributions that demonstrate the effectiveness of multigrid techniques in various contexts are encouraged.

This track focuses on the integration of high-performance computing techniques in numerical methods. Papers that showcase the application of parallel computing and optimization strategies are particularly welcome.