Advanced Computing is a premier gold open access publication dedicated to publishing high-quality research across the full spectrum of computer science, from theoretical foundations and software engineering to AI, computer vision, and emerging technologies. The journal emphasizes interdisciplinary innovation, connecting core computing with systems, networks, graphics, and real-world applications. Through rigorous peer review, it contributes to the responsible evolution of computing technologies, ensuring that our readers stay at the forefront of this rapidly advancing field.

Advanced Computing covers topics that include, but are not limited to:

• Theoretical Computer Science and Algorithms: including but not limited to; algorithm design and analysis, computational complexity, graph theory, optimization methods, formal methods and automata theory.
• Software Engineering and Programming Languages: including but not limited to; software architecture and modelling, benchmarking and evaluation frameworks, programming paradigms and language design, compiler construction and optimization, DevOps and software reliability, fuzzy systems.
• Systems, Networks, and Communication: including but not limited to; architectures, distributed and parallel systems, cloud, cluster, and edge computing, mobile and wireless communication, network protocols and routing, sensor and ad hoc networks, high-performance and supercomputing, Internet of Things (IoT), performance analysis and network control, open-source AI libraries and reproducibility standards, future internet: Blockchain, smart cities, sustainable networking.
• Computer Vision, Graphics, and Imaging: including but not limited to; object detection and recognition, 3D reconstruction and stereovision, image and video processing, augmented and virtual reality (AR/VR), image synthesis and rendering, medical and biological imaging, scene understanding and segmentation, tracking, motion analysis, and animation.
• Artificial Intelligence, Data Science, and Human-Centered Computing: including but not limited to; machine learning, data mining, natural language processing, signal and pattern recognition, cognitive architectures and models of reasoning, data management, big data analytics, governance, human-computer interaction (HCI), visual analytics and visual data science, multimodal learning and interpretation, cognitive & Developmental Systems: Cognitive robotics, developmental AI, human-like learning, affective computing: emotion recognition, multimodal affect sensing.
• Security, Privacy & Cryptography: including but not limited to; cryptographic systems: Symmetric/asymmetric cryptography, post-quantum security, privacy-preserving technologies: federated learning security, anonymization, cybersecurity: threat modeling, intrusion detection, secure architectures.
• Emerging Technologies and Interdisciplinary Applications: including but not limited to; explainable & unexplainable AI, fairness, accountability, and transparency in computing AI, quantum computing, foundation models and large-scale pretraining (LLMs), photonic, bio-computing, and brain-like computing paradigms, neuromorphic and amorphous computing, Internet of Things (IoT).
• Ethical and governance challenges that need to be addressed to ensure responsible use of computing and AI technologies to protect society while encouraging innovation.