7th International Conference on Soft Computing, Artificial Intelligence and Machine Learning (SAIM 2026)

Scope

7^th International Conference on Soft Computing, Artificial Intelligence and Machine Learning (SAIM 2026)

Topics

AI Algorithms, Artificial Intelligence, Automatic Control, Bioinformatics, Biomedical Engineering, CAD Design & Testing

Submission System

Authors are invited to submit papers through the Conference Submission System.

Proceedings

Hard copy of the proceedings will be distributed during the Conference.

Scope

The 7^th International Conference on Soft Computing, Artificial Intelligence and Machine Learning (SAIM 2026) invites high quality research contributions from academia and industry. SAIM has established itself as a forum for presenting cutting edge advances in AI, machine learning, soft computing, and intelligent systems.

SAIM 2026 aims to bring together leading researchers to exchange ideas, discuss innovations, and explore emerging challenges shaping the future of intelligent technologies. We welcome original, unpublished work that pushes the boundaries of theory, methods, systems, and applications.

SAIM 2026 invites submissions on all areas of Artificial Intelligence, Machine Learning, and Soft Computing, including but not limited to:

Foundations of Artificial Intelligence
Machine Learning Theory, Optimization and Algorithms
Deep Learning Architectures and Training Techniques
Reinforcement Learning and Decision Making
Probabilistic Modeling and Bayesian Methods
Trustworthy, Explainable and Interpretable AI
Fairness, Accountability, Transparency and Ethics in AI
Causality in Machine Learning
Continual, Lifelong and Transfer Learning
Multimodal Learning and Foundation Models
Generative AI (Text, Image, Audio, Video)
Autonomous Agents and Multi Agent Systems
Computer Vision and Pattern Recognition
3D Vision, Scene Understanding and Reconstruction
Vision Language Models
Natural Language Processing and Large Language Models
Information Retrieval, Search and Web Intelligence
Knowledge Representation, Reasoning and Knowledge Graphs
Conversational AI and Dialogue Systems
Bioinformatics, Computational Biology and Biomedical AI
AI for Healthcare, Precision Medicine and Medical Imaging
Neurosymbolic and Cognitive Computing
AI for Scientific Discovery, Simulation and Modeling
Data Mining, Big Data Analytics and Scalable ML
Data Visualization and Exploratory Analysis
Social Network Analysis and Computational Social Science
E-commerce, FinTech and Smart Economy Applications
AI for Climate Science, Sustainability and Smart Cities
Distributed, Parallel and High Performance AI Systems
Edge AI, TinyML and Embedded Intelligence
Neuromorphic and Morphic Computing
AI Optimized Hardware and Accelerators
Nano/Micro Systems for Intelligent Computing
Soft Computing Theory and Applications
Fuzzy Logic, Fuzzy Systems and Rough Sets
Evolutionary Computing, Swarm Intelligence and Optimization
Hybrid Intelligent Systems
Robotics, Autonomous Systems and Intelligent Control
Human Robot Interaction and Embodied AI
Cyber Physical Systems and Intelligent Networks
AI Security, Privacy and Adversarial Machine Learning
Robustness, Safety and Reliability of AI Systems
Quantum Machine Learning
Benchmarking, Evaluation and Reproducibility in AI
AI for Creativity, Art, Media and Cultural Analytics