Artificial Intelligence (AI) is rapidly transforming chemical engineering by enabling data-driven decision-making, predictive modeling, and intelligent process optimization. AI-powered algorithms can analyze vast amounts of experimental and operational data to identify patterns, improve reaction performance, and accelerate catalyst discovery. As industries move toward smart manufacturing, AI is becoming an indispensable tool for improving efficiency, reducing costs, and enhancing sustainability.
Recent advancements in machine learning, deep learning, and digital twins are revolutionizing process design and operational management. Researchers are applying AI to catalyst screening, reaction pathway prediction, fault detection, predictive maintenance, and supply chain optimization. The integration of AI with laboratory automation and high-throughput experimentation has significantly shortened research and development cycles while improving the reliability of industrial processes.
This session welcomes contributions on AI applications in catalysis, process engineering, computational modeling, intelligent manufacturing, and industrial automation. Participants will discuss innovative digital solutions that are shaping the future of chemical engineering and supporting the transition toward highly connected, efficient, and sustainable production systems.