AAIA 2025 is the premier international forum for the presentation of new advances and research results in the fields of Artificial Intelligence and Applications. High-quality original submissions are welcome from research results and applications of all areas of AI including but not limited to the following areas:

Topic 1: Machine Learning and Deep Learning
1. New machine learning algorithms or techniques
-Innovative machine learning algorithms and advancements in existing methods.
-Development of novel techniques for model training and evaluation.
-Improvements in algorithm efficiency and scalability.

2. Deep neural network architectures and optimizations
-Research on new neural network architectures like transformers, graph neural networks, etc.
-Optimizing deep learning models for better performance and faster training.
-Techniques for enhancing model interpretability and transparency.

3. Applications of deep learning in transdisciplinary engineering
-Application of deep learning models in infrastructure health monitoring (e.g., bridge crack detection with civil engineering constraints).
-Utilizing deep learning for cross-domain data fusion (e.g., climate prediction via satellite imagery + IoT sensor networks).
-Exploring deep learning applications in smart manufacturing, renewable energy systems, and biomedical engineering.

Topic 2: Computer Vision and Pattern Recognition
1. Image and video processing
-Techniques for object detection, recognition, and segmentation.
-Advances in video analysis, including action recognition and event detection.
-Methods for image enhancement, restoration, and super-resolution.

2. Visual generation and transformation
-Research on generative models like GANs for image and video generation.
-Techniques for style transfer and image-to-image translation.
-3D vision and reconstruction methods from 2D images.

3. Applications in transdisciplinary systems
-Computer vision applications in autonomous driving (e.g., lane detection integrated with traffic flow optimization models).
-Use of computer vision in healthcare and bioengineering (e.g., surgical robotics with real-time biomechanical feedback).
-Implementation of privacy-preserving biometrics in smart city governance and ethical authentication systems.

Topic 3: AI Application and Technology in Industry
1. AI-Driven Innovations in Industry Practice
-Innovative integration of AI techniques to optimize product design and development processes.
-Application of AI methods, such as reinforcement learning and optimization algorithms, to improve manufacturing and operational performance.
-Case studies and pilot projects demonstrating AI applications in real-world engineering contexts (e.g., predictive maintenance, digital twins, and automated quality control).

2. Digital Transformation and Intelligent Systems
-AI-Driven Digital Twins: Construction of digital twins using AI for simulation, real-time analytics, and performance optimization of industrial assets.
-Integration with IoT and Big Data: Merging AI with IoT, sensor networks, and big data analytics to enable smart factories and connected production lines.
-Cyber-Physical Systems: Advancements in cyber-physical systems where AI enhances interaction between physical processes and digital control systems, driving Industry 4.0.

3. Cross-Disciplinary Collaborative Approaches
-Multi-disciplinary research combining AI with fields such as IoT, cyber-physical systems, and materials science to address complex engineering challenges.
-Promoting international collaboration through joint projects and global partnerships that enhance the exchange of knowledge.
-Integration of AI innovations across diverse sectors, including transportation, construction, energy, and healthcare, to drive transdisciplinary solutions.