Hybrid Conferencee

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

10th - 11th June 2026 | Edinburgh, UK
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Conference Brochure
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Edinburgh. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Edinburgh event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Edinburgh conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Edinburgh, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Edinburgh."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICNLAMC aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Numerical Methods, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

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

01
Numerical methods for matrix computations
02
Applications of linear algebra in computing
03
Iterative methods for large matrices
04
Matrix factorization techniques and applications
05
Numerical stability in matrix algorithms
06
Eigenvalue problems in numerical linear algebra
07
Matrix computations in machine learning
08
Parallel algorithms for matrix operations
09
Sparse matrix techniques and applications
10
Numerical methods for structured matrices
11
Matrix computations in optimization problems
12
Applications in data science and analytics
13
Matrix methods for differential equations
14
Numerical methods for singular value decomposition
15
Robustness in matrix algorithms
16
Numerical linear algebra in scientific computing
17
High-performance matrix computations
18
Numerical methods for large-scale systems
19
Recent developments in matrix algorithms
20
Future directions in numerical linear algebra