Paper submission

Submission and Publication

The 2026 International Symposium on Information and Communication Technology (SOICT 2026) welcomes original, unpublished research papers describing theoretical, empirical, conceptual, or experimental work in Computer Science. Submissions must not be under review elsewhere during the evaluation process. The symposium language is English.

Manuscript preparation:
Papers must be formatted according to the Springer CCIS conference template (available in LaTeX or Word format). Detailed instructions and templates can be found at: Springer CCIS Instructions.

Submission system:
All papers must be submitted electronically via the EasyChair system.

Page limit:
Each paper is limited to a maximum of 12 pages (excluding references).

Review style:
SOICT 2026 uses a single-blind review process; author names and affiliations should be included in your submission. Each submission will be evaluated by at least three independent reviewers.

Publication:
Accepted and presented papers will be published in the Springer CCIS Proceedings, indexed by major databases such as Scopus, EI Compendex, and SpringerLink.

Code of Conduct:
Please refer to the Springer Nature Code of Conduct.

SUBMISSION PROCEDURE

Register for an account on EasyChair if you do not already have one.
Submit your manuscript to SOICT 2026 via the EasyChair system.

CONFERENCE SCOPES

Relevant topics include, but are not limited to:

Applied AI, Big Data Analytics, and Data-Driven Applications

This track focuses on applied artificial intelligence, big data analytics, and data-driven solutions for real-world problems. It welcomes research contributions, system designs, industrial applications, and case studies that demonstrate how AI, machine learning, data mining, and large-scale data analytics can be used to improve decision-making, automation, prediction, optimization, and innovation across domains.

The track emphasizes practical AI applications, data-driven methods, scalable analytics, and the deployment of AI-based solutions in industry, government, education, healthcare, finance, transportation, smart cities, agriculture, and other socio-economic sectors.

Topics of interest include, but are not limited to:

Applied machine learning and deep learning
Big data analytics and large-scale data processing
Data mining, knowledge discovery, and predictive analytics
AI applications in industry, government, education, healthcare, finance, agriculture, and smart cities
Decision support systems and intelligent analytics
Data-driven optimization and intelligent decision-making
AI for business intelligence and digital transformation
Recommender systems and personalization
Time-series forecasting and anomaly detection
Graph analytics and knowledge graphs for applications
Natural language processing applications
AI-powered automation and intelligent assistants
Data visualization and visual analytics
Responsible, explainable, and trustworthy applied AI
Evaluation and deployment of AI systems in real-world environments

Multimedia Processing, Computer Vision, and Multimodal Intelligence

This track covers theories, methods, systems, and applications in multimedia processing, computer vision, image and video analysis, speech and audio processing, and multimodal intelligence. It welcomes research on the representation, understanding, retrieval, generation, and interaction of multimedia data, including text, image, video, audio, sensor data, and multimodal streams.

The track also encourages submissions related to emerging multimodal AI systems, vision-language models, multimedia retrieval, human-centered multimedia computing, and intelligent media applications.

Topics of interest include, but are not limited to:

Image, video, audio, and speech processing
Computer vision and pattern recognition
Object detection, tracking, recognition, and segmentation
Image and video understanding
3D vision, scene reconstruction, and visual perception
Multimedia information retrieval and recommendation
Multimodal learning and multimodal representation
Vision-language models and multimodal foundation models
Generative models for image, video, audio, and multimedia content
Human action recognition and behavior analysis
Medical image analysis and biomedical multimedia processing
Remote sensing image analysis
Document image analysis and OCR systems
Augmented reality, virtual reality, and mixed reality
Multimedia security, privacy, watermarking, and forensics
Lifelogging, event retrieval, and personal multimedia analytics
Multimedia applications in education, healthcare, culture, tourism, and smart cities

Communications, Networking, and Cybersecurity

This track addresses advances in communication systems, networking technologies, Internet of Things, cloud-edge infrastructures, distributed systems, and cybersecurity. It welcomes both theoretical and applied research on the design, optimization, management, and security of modern communication and networked systems.

The track also covers emerging topics such as 5G/6G networks, software-defined networking, edge intelligence, secure IoT systems, cyber-physical systems, blockchain-enabled security, privacy-preserving technologies, and resilient digital infrastructures.

Topics of interest include, but are not limited to:

Communication systems and wireless communications
5G, 6G, and beyond networks
Internet of Things and industrial IoT
Sensor networks and cyber-physical systems
Software-defined networking and network function virtualization
Cloud, edge, and fog computing infrastructures
Mobile and ubiquitous computing
Network protocols, architectures, and performance evaluation
Network optimization, resource allocation, and traffic engineering
Distributed systems and decentralized architectures
Blockchain and distributed ledger technologies
Cybersecurity and network security
Cryptography and applied security
Privacy-preserving computing and secure data sharing
Intrusion detection, malware analysis, and threat intelligence
Security of IoT, cloud, edge, and mobile systems
Digital identity, authentication, and access control
Resilience, reliability, and trust in networked systems
AI for networking and cybersecurity
Security governance, risk management, and compliance

AI Foundations, Foundation Models, and Generative AI

This track focuses on the foundations, theories, algorithms, models, and emerging paradigms of artificial intelligence. It welcomes high-quality research on machine learning, deep learning, reasoning, optimization, foundation models, large language models, generative AI, agentic AI, trustworthy AI, and evaluation methodologies.

The track aims to provide a forum for fundamental advances in AI, including both theoretical contributions and methodological innovations that can serve as foundations for future intelligent systems and applications.

Topics of interest include, but are not limited to:

Foundations of artificial intelligence and machine learning
Deep learning theories, architectures, and algorithms
Foundation models and large language models
Generative AI and generative models
Diffusion models, GANs, VAEs, and autoregressive models
Large language model reasoning, planning, and tool use
AI agents and multi-agent systems
Reinforcement learning and decision-making
Knowledge representation and reasoning
Neuro-symbolic AI
Causal learning and causal reasoning
Optimization methods for AI and machine learning
Self-supervised, semi-supervised, and few-shot learning
Continual learning, transfer learning, and domain adaptation
Explainable AI and interpretable machine learning
Trustworthy, safe, fair, and responsible AI
AI alignment, evaluation, and benchmarking
Efficient AI, model compression, and small language models
Federated learning and privacy-preserving machine learning
AI robustness, uncertainty estimation, and out-of-distribution detection

Software Engineering, Trusted Digital Platforms, and Smart Services

This track covers software engineering methods, tools, processes, architectures, and technologies for building reliable, secure, scalable, and intelligent software systems, digital platforms, and smart services. It welcomes research on both traditional and AI-enhanced software engineering, including requirements engineering, software architecture, software testing, DevOps, DevSecOps, MLOps, software analytics, and software maintenance.

The track also focuses on trusted digital platforms, data spaces, interoperable services, blockchain-enabled trust infrastructures, cloud-native systems, smart service ecosystems, and software infrastructures that support the digital economy. It particularly welcomes research on secure and scalable platforms for digital transformation in government, industry, finance, education, healthcare, logistics, smart cities, and society.

Topics of interest include, but are not limited to:

Software Engineering

Requirements engineering and requirements reasoning
Software architecture and design
Software modeling and model-driven engineering
Software testing, debugging, verification, and validation
Program analysis and software verification
Software maintenance, evolution, and reengineering
Software quality, reliability, usability, and maintainability
Empirical software engineering
Mining software repositories and software analytics
Human and social aspects of software engineering
Agile software development and software project management
DevOps, DevSecOps, MLOps, and AIOps
Secure software engineering
Software engineering for cloud-native and microservices systems
Software engineering for AI-based systems
AI-assisted software development
Code generation, code review, bug fixing, and automated program repair
LLMs and AI agents for software engineering tasks

Trusted Digital Platforms, Data Spaces, and Digital Economy

Digital platform architecture and engineering
Trusted and secure digital platforms
Platform ecosystems and digital service ecosystems
Digital economy platforms and data-driven service ecosystems
Cloud-native platforms and service-oriented architectures
Microservices, APIs, and interoperability
Data platforms, data spaces, data fabric, and interoperable data infrastructures
Digital identity, eKYC, authentication, authorization, and trust services
Digital public infrastructure and trusted data exchange frameworks
Blockchain and distributed ledger technologies for digital trust
Smart contracts, verifiable credentials, provenance, and trusted registries
Tokenization, traceability, and auditability in digital platform ecosystems
Privacy-preserving data sharing and secure data collaboration
Platform security, compliance, and risk management
Scalable and resilient software infrastructures
Low-code/no-code platforms
Digital twin platforms and cyber-physical service platforms
Governance of digital platforms, data spaces, and digital services

Smart Services, FinTech, and Digital Applications

Smart services for government, education, healthcare, industry, finance, logistics, and smart cities
FinTech platforms and digital financial services
Open banking, digital payment, digital lending, InsurTech, RegTech, and SupTech systems
Blockchain-enabled financial services and trusted transaction platforms
Data-driven services for the digital economy
Intelligent service engineering and service innovation
AI-enabled digital services
Human-centered digital services
Personalized and adaptive services
Service automation and intelligent workflows
Service quality, reliability, and user experience
Evaluation of digital platforms and smart services
Sustainable and responsible digital service development

Lifelogging, Event Retrieval, and Personal Data Analytics

This track focuses on methods, systems, datasets, and applications for lifelogging, event retrieval, personal data analytics, and human-centered multimedia understanding. It welcomes research on the collection, representation, indexing, retrieval, analysis, and visualization of personal and multimodal data from wearable devices, mobile sensors, cameras, social media, and digital services.

Topics: Lifelogging systems and applications, Event retrieval and event understanding, Personal data analytics and personal informatics, Egocentric vision and wearable data analysis, Multimodal lifelog retrieval, Human activity recognition, Personal knowledge graphs and memory augmentation, Context-aware and location-aware personal data analysis, Privacy, ethics, and security in personal data analytics, Evaluation benchmarks, datasets, and challenges for lifelog retrieval, Human-centered interfaces for personal data search and exploration

Quantum Information

Topics: Quantum error correction, Quantum communication, Quantum algorithms, Quantum cryptography, Quantum simulation, Fault-tolerant quantum computing, Intersection of quantum information and machine learning

REQUIREMENTS

Papers must strictly follow the LNCS/CCIS format rules.
All submissions must be in PDF format and should not include page numbers.
Templates are available: Latex template and Word template

For any questions or clarifications regarding the submission process, please refer to the conference website or contact the Organizing Committee.