CanAI Journal of Biological Sciences The CanAI Journal of Biological Sciences publishes research at the intersection of artificial intelligence and the life sciences. The journal welcomes studies that use AI to advance genomics, proteomics, bioinformatics, ecology, and neuroscience. Contributions may include predictive models of disease spread, machine learning for biodiversity monitoring, or computational approaches that uncover hidden patterns in complex biological systems. By bridging biology with cutting-edge AI, the journal aims to accelerate discoveries that improve health, sustainability, and our understanding of life itself.

CanAI Journal of Chemistry The CanAI Journal of Chemistry focuses on the application of artificial intelligence to chemical sciences. It features work on molecular design, drug discovery, materials chemistry, and computational chemistry enhanced by machine learning. Researchers are encouraged to submit studies that use AI for predicting chemical reactions, optimizing synthesis pathways, and modeling properties of new compounds. By integrating chemistry and AI, the journal seeks to highlight how intelligent systems can reduce experimental costs, speed up discovery, and enable breakthroughs across pharmaceuticals, energy, and industrial chemistry.

CanAI Journal of Civil Engineering The CanAI Journal of Civil Engineering explores how artificial intelligence can transform the planning, design, and maintenance of infrastructure. Topics of interest include AI-driven smart cities, predictive maintenance of roads and bridges, structural health monitoring, and machine learning applications in sustainable urban development. The journal also encourages research on climate resilience, disaster risk reduction, and the integration of AI into construction practices. Its mission is to showcase innovative approaches that improve safety, efficiency, and sustainability in civil engineering.

CanAI Journal of Computer Science The CanAI Journal of Computer Science serves as a platform for advancing the theoretical and applied foundations of artificial intelligence. It publishes work on core areas such as machine learning, deep learning, reinforcement learning, natural language processing, and computer vision, while also emphasizing AI ethics, fairness, and safety. Contributions may range from algorithmic innovations to applied systems in robotics, autonomous decision-making, or distributed AI. The journal’s goal is to provide a space where fundamental research and applied breakthroughs in computer science converge to shape the future of intelligent technologies.

CanAI Journal of Materials Science The CanAI Journal of Materials Science highlights the role of artificial intelligence in accelerating discoveries and innovations in materials research. Submissions may include AI-assisted design of nanomaterials, prediction of material properties, optimization of manufacturing processes, and applications in renewable energy, batteries, and semiconductors. By combining data-driven models with materials science, the journal showcases how AI can reduce trial-and-error experimentation and open new pathways for creating stronger, more efficient, and more sustainable materials.

CanAI Journal of Psychology The CanAI Journal of Psychology explores the dynamic relationship between artificial intelligence and the study of human behavior and cognition. The journal publishes research on computational models of psychological processes, AI-assisted mental health assessment, and human–AI interaction. It also encourages work on the ethical and societal implications of AI in psychology, including issues of trust, bias, and wellbeing. By uniting psychology with intelligent systems, the journal aims to deepen our understanding of both human minds and the responsible design of AI that interacts with them.