Data-Driven Machine Learning Applications in Thermochemical Conversion Processes

• Presents a comprehensive perspective by integrating the disciplines of geology, engineering, policy, and economics to provide a nuanced, comprehensive volume on the subject
• Bridges the gap between data science and thermochemical process engineering
• Spans foundational features and digs deeper on root causes and remedies to challenges and limitations to yield a practical publication for a varied audience
• Uses cutting-edge characterization and modelling tools along with novel methodologies to make the subject practical, easy-to-understand and implement
• Serves as a valuable resource for professionals, researchers, students, educators, and policymakers

Jude Okolie is an Assistant Professor of Chemical Engineering at Bucknell University. He previously served as an Assistant Professor of Engineering Pathways at the University of Oklahoma. His research focuses on the thermochemical conversion of waste materials into green fuels and the utilization of hydrochar, biochar, and activated carbon for environmental remediation. His work also involves the application of process simulation, artificial intelligence, and machine learning to address challenges related to climate change, environmental pollution, and sustainable agriculture.

Dr. Adewale Giwa is a faculty member in the Chemical and Water Desalination Engineering Program at the University of Sharjah, UAE. He specializes in Chemical Engineering and Industrial Chemical Processes, teaching courses on fluid mechanics, thermal sciences, and system design. His research focuses on membrane technologies, sustainable water treatment, and the integration of renewable energy in chemical processes. Dr. Giwa has authored over 90 peer-reviewed publications and secured over $3 million in research funding. Recognized as a top scientist globally, he is currently leading a project with IBM to enhance water access monitoring and forecasting.