Special Sessions

Human-AI collaboration in decision support refers to the partnership between humans and artificial intelligence systems to enhance decision-making processes. These systems aim to combine human intuition and domain expertise with AI & data-driven analysis and speed. Collaboration can be either sequential (AI suggests, human decides) or interactive (continuous feedback between both). Trust, transparency, and explainability are essential for effective teamwork. Such systems are used in high-stakes fields like healthcare, finance, legal, defense, and education. They help reduce human bias, cognitive overload, and errors in complex scenarios. AI tools may offer predictions, recommend options, or highlight risks to support users. The human remains accountable, while the AI provides augmented intelligence rather than replacing human judgment. Successful collaboration requires designing interfaces that are user-friendly and ethically aligned. Ultimately, the goal is to make decisions that are faster, fairer, and more informed through human-AI synergy.

Topic of Interest (but not limited to):

• Design of Explainable AI Systems for Collaborative Decision-Making
• Cognitive Load Optimization in Human-AI Decision Systems
• AI-Augmented Decision Support in Education and Learning Analytics
• Ethical Frameworks for Shared Decision-Making with AI
• Human-AI Collaboration in Clinical Decision Support Systems

This special session aims to spotlight cutting-edge research at the intersection of Artificial Intelligence (AI), Internet of Things (IoT), Cybersecurity, and Digital Twin technologies, unified under the theme Cognitive Systems & Secure Twins. With intelligent systems increasingly integrated into critical infrastructure, the demand for secure, adaptive, and intelligent architectures is more urgent than ever. This session invites contributions that demonstrate how AI can be used to build cognitive frameworks enhancing situational awareness, system autonomy, and robust cyber defense. It also highlights how Digital Twins, empowered by AI, can act as real-time simulators for cyber-physical systems, enabling proactive monitoring and anomaly detection across IoT networks.

Topic of Interest (but not limited to):

• Cognitive AI for Edge and Fog Computing
• AI-Driven Intrusion Detection Systems (IDS)
• Digital Twins for Threat Modeling and Security Simulation
• Secure Federated Learning in IoT
• Blockchain-Enabled IoT Security Frameworks
• Quantum-Resistant Algorithms for IoT Security
• Self-Adaptive Cyber Defense Systems
• Digital Twin Applications in Smart Cities, Energy, and Healthcare
• Real-Time Anomaly Detection and AI-Based Risk Assessment
• Secure Multi-Agent Systems and Collaborative Intelligence
• Ethical and Regulatory Aspects in Cyber-Intelligent Systems

This special session will focus on practical skills and research advancements in Vision and Speech based Interactive Technologies

Topics of Interest

• Vision-based interaction – gesture recognition, eye tracking, facial expression/emotion detection, AR/VR vision systems.
• Speech-based interaction – automatic speech recognition, speech synthesis, dialogue systems, voice-based authentication, speech recognition, speaker verification, conversational agents.
• Vision–speech fusion – multimodal HCI frameworks, multimodal learning, adaptive interfaces.
• Multimodal interaction – fusion of vision and speech for adaptive interfaces,
• Generative AI applications for multimodal HCI.
• Assistive technologies for accessibility, healthcare, and education.
• Ethical, privacy, and security issues in multimodal HCI.

Edge-AI is rapidly evolving into a game-changing technology because it enables low-latency, privacy-preserving, and real-time intelligent applications at the edge without relying on cloud servers. In order to share cutting-edge Edge-AI research, architectures, frameworks, and implementations for HCI systems, this event aims to bring together researchers, practitioners, and industry people. This session focuses on integrating Edge Artificial Intelligence (Edge-AI) with real-time human–computer interaction (HCI) using resource-constrained edge devices such as the Raspberry Pi, NVIDIA Jetson Nano, and NVIDIA Jetson Xavier.

Topic of Interest (but not limited to):

• Cutting-edge AI HCI designs for the Jetson Nano, Jetson Xavier, and Raspberry Pi.
• Low-power devices that process speech, image, and video signals in real time.
• Implementing and refining machine learning and deep learning algorithms for embedded devices.
• Compact and lightweight models (model distillation, quantization, TinyML, and pruning).
• Comparing the memory footprint, scalability, energy efficiency, and latency of edge devices.
• Applications of edge-AI in biometrics, assistive technologies, surveillance, and adaptive healthcare.
• Security and privacy issues with decentralized real-time human-machine communication.
• Real-world deployment examples and case studies related to intelligence Edge Ai based HCI applications.

Human computer interfaces are becoming more and more advanced, AI-powered, and impressive. But how to effectively design and implement advanced HCI systems for difficult to reach target groups? What are fruitful methodologies here? And what is different in design advanced HCIs from more traditional and straightforward User Interfaces? In this session, we tackle these questions from multiple viewpoints and cases. We learn how end user involvement, and sound methodologies shed light on effective and valid designs of advanced HCIs. This special session aims to spotlight cutting-edge research and methodologies in the HCI field. It also highlights how challenging user groups should be involved in designing effective HCIs. Participants will enrich their methodological toolkit and be inspired by approaches beyond the desk and outside the ivory tower.

Topic of Interest (but not limited to):

• AI-Driven human computer interaction (HCI)
• Usability and User evaluation of advanced HCI
• Methodologies involving end users in HCI design
• Advanced applications in HCI
• Lessons learned from HCI tests
• Fieldwork in intelligent human computer interaction
• Design trajectories and interations