International Conference on Applied Linear Algebra & Machine Learning

International Conference on Applied Linear Algebra & Machine Learning (ICALAML 2026)

Date: June 6, 2026
Organized by: TEMS Tech Solutions
Conference Mode: Hybrid
Convenor: Ms. Suguna Balan, Co-Founder & Director, TEMS Tech Solutions

1] Conference Introduction

The International Conference on Applied Linear Algebra & Machine Learning (ICALAML 2026) provides a premier forum for researchers, data scientists, mathematicians, engineers, and AI practitioners to explore the synergy between linear algebra and machine learning.

Linear algebra forms the mathematical foundation of most machine learning algorithms, including deep learning, optimization methods, and data representation models. ICALAML 2026 aims to bridge the gap between theoretical mathematics and practical AI applications, fostering innovations in areas like predictive modeling, computer vision, natural language processing, and scientific computing.

The conference encourages interdisciplinary discussions and promotes the integration of mathematical rigor with AI-driven solutions to tackle real-world problems.

2] Conference Objective

• To explore the mathematical foundations of machine learning using linear algebra.

• To showcase practical applications of linear algebra in deep learning, optimization, and AI algorithms.

• To provide a platform for interdisciplinary collaboration among mathematicians, AI researchers, and engineers.

• To highlight recent advances in matrix computations, tensor analysis, and numerical methods for ML.

• To encourage high-quality publications in indexed journals.

3] Conference Outcome

Participants will gain:

• Advanced knowledge of linear algebra applications in machine learning and AI.

• Insights into state-of-the-art algorithms, tensor decomposition, and dimensionality reduction techniques.

• Opportunities to publish research in Scopus/WoS/SCI indexed journals.

• Networking with global experts in mathematics, data science, and AI.

• Exposure to real-world case studies in AI, engineering, finance, and scientific computing.

4] Call for Papers – List of Topics

Authors are invited to submit original research on (but not limited to) the following topics:

Applied Linear Algebra

• Matrix and Tensor Computations

• Eigenvalues, Eigenvectors & Spectral Analysis

• Matrix Factorization & Decomposition Techniques

• Numerical Linear Algebra for Large-Scale Problems

• Linear Systems, Optimization & Sparse Matrices

Machine Learning & AI

• Deep Learning & Neural Networks

• Dimensionality Reduction Techniques (PCA, SVD, ICA)

• Reinforcement Learning & Optimization Algorithms

• Kernel Methods & Support Vector Machines

• Graph-Based Machine Learning Models

Interdisciplinary Applications

• AI in Computer Vision & Image Processing

• NLP and Text Mining using Linear Algebra

• Data Analytics & Predictive Modeling

• Scientific Computing & Engineering Applications

• Financial Modeling & Risk Analytics

Case Studies & Industry Applications

• Real-World AI Implementations

• Large-Scale Data Analysis

• Optimization for Industrial and Research Applications

5] About TEMS Tech Solutions

TEMS Tech Solutions is a leading Technology & AI Consulting Startup committed to delivering innovative solutions in AI, data analytics, machine learning, software development, IoT, and cybersecurity.

We empower research communities, academic institutions, and industries by:

• Bridging mathematics and AI through applied research

• Providing AI-driven technological consulting and solutions

• Conducting workshops, conferences, and training programs

• Facilitating interdisciplinary collaborations and innovation

6] Estimated Important Dates

7] Registration Fees

Registrations are accepted on a first-come, first-served basis.

Foreign Delegates

• 100 USD

Indian Delegates

• Students/Scholars: 1000 INR (Late Fee: 1500 INR)

• Faculty: 2000 INR (Late Fee: 2500 INR)

• Industry/Scientists: 3000 INR (Late Fee: 3500 INR)

Payment Links

• India: https://rzp.io/rzp/HQcB9qw

• Foreign Delegates: https://www.paypal.com/ncp/payment/PTBJETYTME7E8

8] Publication

Selected papers will be considered for publication in Scopus, WoS, and SCI indexed journals, depending on peer review and journal guidelines.

Recommended Journals (Applied Linear Algebra & Machine Learning Focus)

1. Linear Algebra and Its Applications (Elsevier)

   • ISSN: 0024-3795

   • Link: https://www.journals.elsevier.com/linear-algebra-and-its-applications

2. Journal of Machine Learning Research (JMLR)

   • ISSN: 1532-4435

   • Link: https://www.jmlr.org

3. Applied Numerical Mathematics (Elsevier)

   • ISSN: 0168-9274

   • Link: https://www.journals.elsevier.com/applied-numerical-mathematics

4. Neural Computing & Applications (Springer)

   • ISSN: 0941-0643

   • Link: https://www.springer.com/journal/521

5. Pattern Recognition Letters (Elsevier)

   • ISSN: 0167-8655

   • Link: https://www.journals.elsevier.com/pattern-recognition-letters

9] Contact Details

Email: contact@temstechsolutions.com
Registration Links:

• India: https://rzp.io/rzp/HQcB9qw

• Foreign Delegates: https://www.paypal.com/ncp/payment/PTBJETYTME7E8