CALL FOR PAPER

The International Conference on Artificial Intelligence, Data Science and Intelligent Engineering (AIDSIE 2025) aims to showcase the latest research achievements, methodological advancements, and industrial innovations in the fields of artificial intelligence, data analytics, and intelligent engineering systems. The conference serves as a global forum for researchers, engineers, and practitioners to exchange ideas, discuss emerging technologies, and foster collaboration that drives intelligent transformation in science and engineering.

AIDSIE 2025 provides an interdisciplinary platform that bridges theoretical foundations with real-world applications, emphasizing the integration of AI, big data, and engineering intelligence to solve complex challenges. Researchers are encouraged to present novel algorithms, analytical models, and engineering frameworks that enhance efficiency, adaptability, and sustainability across diverse domains.

We welcome original research papers, case studies, and comprehensive reviews that contribute to the advancement of artificial intelligence, data science, and intelligent engineering.
Topics of interest include, but are not limited to:

1. Artificial Intelligence Foundations and Intelligent Systems

  • Deep learning architectures and transformer-based models
  • Explainable, trustworthy, and human-aligned AI
  • Multimodal and cognitive computing frameworks
  • Generative AI and large language models (LLMs)
  • Adaptive and self-evolving neural networks
  • Knowledge representation, reasoning, and hybrid intelligence
  • AI ethics, governance, and responsible innovation
  • Cognitive robotics and autonomous decision-making

2. Data Science, Analytics, and Computational Intelligence

  • Data mining, knowledge discovery, and pattern recognition
  • Big data processing, visualization, and decision support
  • Statistical learning and high-dimensional data analysis
  • Time-series modeling and predictive analytics
  • Federated learning and distributed AI systems
  • Optimization algorithms and metaheuristic computation
  • Evolutionary computation, swarm intelligence, and reinforcement learning
  • Uncertainty quantification and stochastic modeling

3. Intelligent Engineering and Automation Technologies

  • Smart manufacturing and industrial AI applications
  • Intelligent control systems and adaptive automation
  • Digital twin modeling and simulation-based engineering
  • Cyber-physical systems and intelligent robotics
  • Sustainable and energy-efficient engineering design
  • Human–machine collaboration and augmented intelligence
  • Fault diagnosis, predictive maintenance, and reliability engineering
  • Intelligent optimization in civil, mechanical, and electrical engineering

4. Emerging Technologies and Cross-disciplinary Applications

  • AI in healthcare, biomedical data analysis, and precision medicine
  • Intelligent transportation systems and autonomous vehicles
  • AI-enhanced education, e-learning, and virtual classrooms
  • Financial technology, risk modeling, and algorithmic trading
  • Cloud computing, edge intelligence, and Internet of Things (IoT)
  • Secure and privacy-preserving data processing
  • AI for climate modeling, environmental monitoring, and sustainability
  • Quantum computing, neuromorphic hardware, and future AI paradigms