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International Conference on Numerical Linear Algebra and Matrix Computations (ICNLAMC-26)

29th - 30th Sep 2026,San Francisco, USA

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Call for Paper

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Important Dates


Early Bird Registration

30th Aug 2026

Paper Submission Deadline

4th September 2026

Registration Deadline

14th September 2026

Conference Date

29th - 30th Sep 2026

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  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in San Francisco conference.
  • Peer Review Process:
    The peer review process will begin soon for San Francisco conference.
  • Networking with Global Experts:
    Join global experts at our conference in San Francisco.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Call For Papers

The ICNLAMC bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Numerical Linear Algebra and Matrix Computations, encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Numerical methods for matrix computations
  • Applications of linear algebra in computing
  • Iterative methods for large matrices
  • Matrix factorization techniques and applications
  • Numerical stability in matrix algorithms
  • Eigenvalue problems in numerical linear algebra
  • Matrix computations in machine learning
  • Parallel algorithms for matrix operations
  • Sparse matrix techniques and applications
  • Numerical methods for structured matrices
  • Matrix computations in optimization problems
  • Applications in data science and analytics
  • Matrix methods for differential equations
  • Numerical methods for singular value decomposition
  • Robustness in matrix algorithms
  • Numerical linear algebra in scientific computing
  • High-performance matrix computations
  • Numerical methods for large-scale systems
  • Recent developments in matrix algorithms
  • Future directions in numerical linear algebra

Assessment

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Submit Your Paper Now Confirm Your Participation Today

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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