Call for Papers

Prospective authors are kindly encouraged to contribute original and unpublished research in Meta-Heuristic Algorithms, Software Engineering, AI, and contemporary applications.

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Guidelines

Submission Process

The submission and review process for METASOFT 2026 will be conducted via Microsoft CMT, an online manuscript management portal. Authors must upload their abstracts and full manuscripts on or before the deadline.

Plagiarism Policy: The similarity index of submitted manuscripts must strictly be below 15%. Authors can track their paper review status through their registered CMT account.
*The Full-length Paper is approximately of 10 pages for Submission.

Peer Review

Review Process & Policy

All submitted manuscripts will undergo a rigorous double-blind peer review process by anonymous international expert reviewers managed through the CMT system.

High-quality contributions describing original work (conceptual, empirical, experimental, or theoretical) are cordially invited for presentation.

Authors

Call for Contributions

Authors are invited to submit original research papers, abstracts, and e-posters presenting novel ideas, methodologies, and applications related to the conference themes.

The conference also offers opportunities for technical discussions, networking, and collaboration across the featured technical tracks.

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Scope & Topics

Technical Conference Tracks

Track 1

Meta-Heuristic Mathematical Algorithms & Its Applications

Addressing foundational and novel metaheuristic search strategies in complex engineering problems.

Genetic & Evolutionary Algorithms
Swarm Intelligence Optimization
Particle Swarm & Ant Colony Optimization
Simulated Annealing & Tabu Search
Hybrid Metaheuristics
Metaheuristics in Software Architecture

Track 2

Multi-Objective Optimization in Software Testing

Application of optimization algorithms in quality assurance, automated test suite generation, and software reliability.

Techniques in Software Testing
Regression Testing & Test Prioritization
Continuous Integration Pipelines
Functional & GUI Testing
Load & Performance Testing
Unit Testing Optimization
Data-driven & Keyword-driven Testing

Track 3

AI/ML & Its Applications in Engineering

Advances in neural models, deep learning, fuzzy logic, and intelligent domain applications.

Neural Networks & Deep Learning
Fuzzy & Neuro-Fuzzy Systems
Bio-medical Signal & Image Processing
Speech Processing & Recognition
Biotechnology Applications
Intelligent Communication Systems

Track 4

Other Applications in Mathematical Engineering

Broad domain applications spanning computer vision, NLP, IoT, and computational science.

Data Science & Data Engineering
Internet of Things (IoT / IoE)
Bioinformatics & Healthcare Analytics
Computer Vision & Object Recognition
Natural Language Processing (NLP)
Human Activity Recognition
Climate Science Computing