Integrate AI into chemical research through structured tutorials and exercises

Chemists adopting AI methods need discipline-specific training beyond generic introductions. Artificial Intelligence in Chemistry and Chemical Engineering: From Basics to Practical Exercises provides a step-by-step tutorial guiding researchers through AI, automation, data science, and cheminformatics. Progressing from foundational concepts to advanced applications, hands-on exercises and real-world case studies enable direct application to ongoing research programs.

Coverage spans AI reaction prediction models, automated high-throughput synthesis platforms, and chemical reaction big data systems. The book addresses ethical implications and regulatory considerations for AI deployment in chemistry. A companion website and a specialized large language model deliver continuous interactive support, providing updated resources and ongoing learning opportunities beyond the printed text.

Readers will also find:

• Foundational machine learning concepts tailored specifically for practitioners working in chemistry and chemical engineering research disciplines
• Detailed tutorials on building and utilizing chemical reaction big data systems for accelerating discovery and optimizing workflows
• Real-world case studies demonstrating how AI-driven approaches solve specific challenges in organic synthesis and molecular science
• Discussion of potential misuse scenarios and regulatory frameworks to navigate responsible AI integration in laboratory settings
• Practical guidance on constructing next-generation automated high-throughput synthesis platforms for efficient experimental design and execution

Designed for organic, physical, theoretical, medicinal, analytical, pharmaceutical, and environmental chemists, as well as materials scientists, chemical engineers, and computer scientists, this book delivers the structured training required to apply AI methods directly to chemical research and industrial practice.

Kuangbiao Liao is a Principal Investigator at the Guangzhou National Laboratory, a member of the All-China Youth Federation, and a standing member of the Guangzhou Association for Science and Technology. His research focuses on AI chemistry, including automated high-throughput synthesis platforms, chemical reaction big data systems, artificial intelligence reaction prediction models, and new methodologies for organic synthesis. He previously worked at AbbVie Pharmaceuticals before returning to China.