Call for Papers

IDCW-2026 (Intelligent Digitalization Conference – Winter)

Aim

Digital transformation is reshaping organizations and economies by driving forward technologies such as artificial intelligence (AI), the Internet of Things (IoT), cloud computing, and intelligent data analytics. Innovative concepts like Digital Twins—virtual representations for intelligent systems—open up new possibilities for improving efficiency and gaining deeper insights into complex systems.

Advances in AI, such as Deep Learning and Transformer Models, are driving intelligent systems and innovative applications, unlocking new possibilities across industries.

Federated Machine Learning offers a decentralized approach to AI training, enabling privacy-preserving collaboration across distributed systems.

In this dynamic landscape, cybersecurity plays a critical role in safeguarding digital transformation initiatives. Key areas such as threat detection and mitigation, threat intelligence, data encryption and privacy, and ensuring security in IoT and cloud ecosystems are essential to protecting digital infrastructures. Furthermore, enhancing resilience in digital product systems is vital to ensure the reliability and continuity of operations in increasingly interconnected environments.

These technologies and security frameworks not only lay the foundation for future-oriented digital architectures, smart products and services, and new business models but also ensure that data-driven innovation occurs in a secure, privacy-conscious manner. By integrating automation, intelligence, and human-centric approaches, digital transformation—underpinned by robust cybersecurity—redefines the economy while contributing significantly to the development of a sustainable, resilient, and secure society.

Scope

We invite local student papers (Scientific Publishing) on the following topics, including related areas:

• Transformer Architecture and Models
• Post-hoc Explainability (z. B. LIME, SHAP)
• Edge Computing
• Regulatory Compliance (EU AI Act)
• Industry 5.0
• IoT Integration
• On Device Use of AI
• Explainable AI and Transparency
• Human-Machine Interaction
• Virtual Representations
• Data Curation
• Machine Learning
• Deep Learning
• Federated Learning
• Neural Networks
• Anomaly Detection
• Adversarial Robustness
• Threat Detection and Mitigation
• AI Security
• Meta-Learning
• Agentic AI
• AI Agents
• Multi-Agent Systems
• Agent Collaboration
• Agentic Decision Support
• Diagnostics AI Agents in Medical Imaging
• Anomaly Detection
• Pattern Recognition
• Edge Inference
• Medical Diagnostics
• Medical Image Processing
• Privacy, Security and Explainable AI
• Intelligent Workflows
• AI-enabled Business Model Innovation
• Operational Innovation
• Intelligent Process Automation
• Artificial Intelligence in Automotive Systems
• Actors and Sensors
• Monitoring
• Large Language Models (LLM)
• Personalization and User Models
• Adaptive Systems
• Driver Experience
• Context Architecture and Prompting
• Failure Analysis
• Diagnostic Agent

Submission Guidelines and Review Process

The scientific paper should not exceed 8 pages in English and must be formatted according to the instructions of Springer: Springer Guidelines.

Authors are invited to submit original, unpublished papers that are not under review for another conference, workshop, or journal at the time of submission. The contributions should address one or more research areas listed above. You can simply update your original submission in EasyChair by selecting “update”, but please do not make a new submission for a newer version of your original submission.

Submission Page:  https://easychair.org/conferences/?conf=idcw2026

Submitted papers will undergo a peer review by at least two members of the program committee. Prior to submission for reviews, please ensure that you have removed any information that could identify the authors. The final camera-ready version should include all authors in alphabetical order as well as the corresponding affiliation.

Organization

Chair: Alfred Zimmermann, Reutlingen University, Herman Hollerith Research Center Böblingen

alfred.zimmermann@reutlingen-university.de