Explore paper tracks, research areas, and our distinguished technical program committee.
We invite high-quality original research contributions across four thematic tracks.
This track focuses on core advances in intelligent computation, spanning machine learning, deep learning, natural language processing, computer vision, and generative models. We encourage work that improves accuracy, robustness, interpretability, and efficiency, as well as research that bridges theory and deployment in real environments. Topics include trustworthy AI, multimodal learning, retrieval and reasoning, reinforcement learning for decision making, and scalable training and inference for practical systems.
This track highlights methods and applications that turn data into actionable insight. Contributions may cover big data management, data mining, statistical modeling, predictive analytics, and visual analytics for exploration and communication. We welcome end-to-end solutions, including data collection, cleaning, feature engineering, model selection, evaluation, and monitoring in production. Emphasis is placed on reproducibility, fairness, privacy-aware analytics, and domain-focused case studies that demonstrate measurable impact.
This track covers intelligent autonomy in robots and cyber-physical systems, from perception and mapping to planning, control, and safe decision making. Topics include self-driving vehicles, drone systems, multi-agent coordination, sensor fusion, SLAM, motion planning, and learning-based control. We also encourage work on human-robot interaction, verification and safety assurance, and real-world deployment challenges such as uncertainty handling, robustness, and resource constraints in embedded platforms.
This track addresses secure, resilient, and energy-aware digital infrastructure. Submissions may explore cybersecurity, privacy-preserving systems, cloud and edge computing, IoT security, blockchain applications, and secure software engineering. We also welcome research on sustainable computing, including energy-efficient architectures, green data centers, workload optimization, and carbon-aware scheduling. The goal is to develop systems that remain dependable under attack and scale responsibly while meeting performance and sustainability demands.
Key leadership roles supporting ICICDAS 2026.
Vice Chancellor MUST
Dean Faculty of Health & Medical Sciences & Chairman CS & IT Department
sobia.csit@must.edu.pk