Nuclear Fusion Powered by AI and HPC
This talk presents advanced simulations with AI-driven optimization to improve the performance of a next-generation plasma-jet-driven magneto-inertial fusion concept.
Overview
Nuclear fusion, once a distant dream, is rapidly moving toward commercial reality. Over the last few years the field has seen an unprecedented acceleration, marked by a sharp rise in private companies and multibillion-dollar investments reported by the Fusion Industry Association. Unlike nuclear fission, which releases energy by splitting heavy isotopes in a chain reaction, fusion generates power by merging light isotopes such as forms of hydrogen, offering a fundamentally safer and cleaner path to energy generation. Today, a wide range of concepts are being explored: from large tokamaks like ITER in France and stellarators such as W7-X in Germany, to compact field-reversed configurations, magnetic-mirror systems, and other innovative ideas. Fusion promises a major contribution to solving the climate crisis, and the possibility of enabling long-distance space travel. Its momentum is strongly supported by Big Tech companies seeking clean energy for growing AI demands, while AI itself is becoming an essential tool for designing more efficient fusion devices. In our group, we combine advanced simulations with AI-driven optimization to improve the performance of a next-generation plasma-jet-driven magneto-inertial fusion concept.
Presenters
Brief Biography
Dr. Vladimir Pimanov is a Postdoctoral Fellow at KAUST working on computational plasma physics and high-performance scientific computing under Prof. David Keyes. He earned his Ph.D. at Lomonosov Moscow State University.