3rd Edition of Global Conference on Biofuels and Bioenergy
September 17-19, 2026 | Rome, Italy
AI & Machine Learning Applications in Bioenergy
The adoption of AI & machine learning applications in bioenergy is transforming efficiency and decision-making in renewable fuel production. Machine learning algorithms optimize biomass conversion processes, predict energy yields, and improve feedstock logistics. AI-driven automation is enhancing reactor control, enzyme engineering, and microbial strain selection for biofuel synthesis. Predictive modeling is also aiding in policy development and market forecasting for bio-based energy. Real-time monitoring and process automation powered by AI are reducing operational costs while improving system adaptability. As big data analytics and deep learning advance, AI-driven solutions are expected to revolutionize bioenergy supply chains and production strategies.
Dai Yeun Jeong
Asia Climate Change Education Center, Korea, Republic of
David Galan Madruga
Carlos III Health Institute, Spain
Sanjeev Gajjela
Tomato Sustainables LTD, United Kingdom
Suzana Borschiver
Federal University of Rio de Janeiro, UFRJ, Brazil
Delia Teresa Sponza
Dokuz Eylul University, Turkey
Tirath Raj
University of Illinois Urbana Champaign, United States
Maren Pauly
SGS Beta, United StatesSubmit your abstract Today
Title : Mixed Culture Fermentation (MCF) for Sustainable Lactic Acid Production for Polylactic Acid (PLA)
Arindam Chakraborty, Natures Principles, India
Title : A strategic technological roadmap for the future of biodiesel: Catalytic innovation and process intensification.
Suzana Borschiver, Federal University of Rio de Janeiro, UFRJ, Brazil
Title : Biofuel production from waste plastics
Delia Teresa Sponza, Dokuz Eylul University, Turkey
Title : Rethinking the iLUC factor in sustainable aviation fuels
Jorge Antonio Hilbert, Energy and Environmental Consulting Services, Argentina
Title : Hydrogen production from contaminated residual biomass: An integrated gasification and SEWGS process study
Enrico Paris, CREA-IT, Italy
Title : Robust MPPT-based design and simulation of integrated solar PV–hydrogen production systems
Elkhatib Kamal, Ecole Centrale de Nantes, France