The 26th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2025) will be held in Gold Coast, Australia. Since its inception in Hong Kong in 2000, PDCAT has established itself as a premier international forum for scientists, engineers, and practitioners to share the latest advances, research results, innovative ideas, developments, and applications in the fields of parallel and distributed computing. Over the past 25 years, PDCAT has been successfully hosted in numerous cities across Asia-Oceania, including locations in Japan, China, Singapore, Australia, New Zealand, and Korea. PDCAT 2025 continues this tradition, providing an engaging platform for fostering collaboration, disseminating cutting-edge research, and exploring emerging trends in parallel and distributed computing and their applications across diverse domains. We warmly welcome researchers and professionals worldwide to join us on the beautiful Gold Coast for this exciting event.

Conference Format: The conference will be held in person, with support for virtual attendance via live online presentations.

We look forward to your valuable contribution and active participation. All accepted and presented papers will be published in the Lecture Notes in Computer Science (LNCS) series by Springer. Selected papers presented at the conference will be invited for extended publication in special issues of SCI-indexed journals. Here is a tentative list of journals:

Tsinghua Science and Technology (Impact Factor: 5.2)
Human-centric Computing and Information Sciences (Impact Factor: 3.9)
Computers and Electrical Engineering (Impact Factor: 4.0)
CCF Transactions on High Performance Computing (Impact Factor: 1.3)


We invite submissions of original and unpublished research on, but not limited to, the following topics:

Networking and Architectures
Parallel and distributed architectures
Interconnection networks
Heterogeneous and multimedia systems
Reliability, availability, and fault tolerance
Ubiquitous and pervasive computing systems
ATM and high-speed networks
Computer networks and optical networks
Communication and telecommunication systems
Wireless networks and mobile computing
Internet of Things (IoT)
Cloud and grid computing systems
Edge and fog computing
Reconfigurable computing architectures
Algorithms and Applications
Artificial Intelligence algorithms
Database systems and data mining
Intelligent computing and neural networks
Parallel and distributed algorithms
Big data computing and analytics
Distributed data and knowledge-based systems
Image processing and computer graphics
High-performance scientific computing
Reconfigurable high-performance computing systems
Resource allocation and management
Network routing and communication algorithms
Bioinformatics and computational biology
Software Systems and Technologies
Task mapping and job scheduling
Formal methods and programming languages
Internet computing and applications
Quantum computing and algorithms
Image processing and computer vision
Agent-based technologies
Operating systems and system software
Software tools and development environments
Parallelizing compilers and optimization
Web services and distributed applications
Component-based software technologies
Simulation, modeling, and visualization
Security and Privacy
Distributed federated learning paradigms
Quantum-enabled federated learning frameworks
Privacy-preserving mechanisms for artificial intelligence
Security of artificial intelligence systems
Privacy-preserving crowd intelligence
Attack and defense algorithms in federated learning
Attack and defense strategies for edge computing
Quantum-based defense mechanisms in federated learning paradigms
Privacy-preserving computation techniques
Database security and cloud security
Access control, authorization, and biometric security
High-Performance Systems
Operating systems for parallel and distributed systems
High-performance computer arithmetic
Memory hierarchy and caching
Performance tuning, optimization, and profiling
Human-computer interaction in parallel and distributed systems
Photonic and quantum computing
Media computing in parallel and distributed systems
Software engineering for parallel and distributed systems
Big Data Management and Processing
Massive data stream processing in cloud environments
Graph analytics, social networks, and the semantic web
Data systems for knowledge discovery, data mining, and machine learning
Big data models and computational theory
Crowdsourced and collaborative data management
Distributed, decentralized, and parallel data management, including blockchain systems
Processing and analytics for graphs, social networks, and semantic web data
Security, privacy, and ethics in data and analytics
Multi-source data processing and integration
Deep learning models and applications