About the Journal

The International Conference on Advanced Technologies, Learning Algorithms, and Systems (ATLAS) is an international forum dedicated to sharing knowledge, latest research findings, and innovations in theory, methodology, and applications of cutting-edge technologies, learning algorithms, and intelligent systems. This conference aims to bridge the gap between academic and professional communities, promote cross-disciplinary collaboration, and foster innovation in the field of learning technologies and intelligent systems.
ATLAS provides a platform for presentation, discussion, critique, exchange of innovative ideas, and current challenges in research and applications of advanced technologies and learning algorithms. The conference serves as a venue for researchers, academics, industry practitioners, and students from around the world to interact and establish potential future collaborations.

Focus and Scope

ATLAS covers various topics related to advanced technologies, learning algorithms, and intelligent systems, including but not limited to:
Advanced Technologies
Distributed computing and cloud computing
Internet of Things (IoT) and cyber-physical systems
Blockchain technology and its applications
Quantum computing and its applications
5G/6G technology and advanced wireless communications
Embedded systems and real-time applications
Advanced software development technologies
Learning Algorithms
Machine learning and computational learning theory
Deep learning and neural networks
Online learning algorithms and theory
Unsupervised, semi-supervised, and active learning
Optimization methods for learning
Reinforcement learning and control
Adaptive learning and recommendation systems
Robustness of learning algorithms against adversarial agents
Intelligent Systems
Artificial intelligence-based systems
Intelligent decision support systems
Big data analytics and data mining
Computer vision and image processing
Natural language processing and text analysis
Robotic systems and intelligent automation
Security and privacy of intelligent systems
Multi-agent systems and collaborative computing
Interdisciplinary Applications
Applications in education and e-learning
Applications in healthcare and bioinformatics
Applications in intelligent transportation
Applications in smart cities and infrastructure
Applications in smart manufacturing
Applications in energy and environment
Applications in cybersecurity
Social and Ethical Aspects
Fairness and transparency in intelligent systems
Data privacy and security
Social impact of advanced technologies
Policies and regulations for advanced technologies
Ethics in artificial intelligence and machine learning