Data-Driven Modeling and Sparse Sensing for Nuclear Energy Systems

Learn about data-driven modeling approaches and sparse sensing techniques specifically applied to nuclear energy systems in this 14-minute workshop talk. Explore how modern computational methods can be leveraged to improve monitoring, control, and optimization of nuclear power systems through advanced sensing strategies and mathematical modeling frameworks. Discover the intersection of data science and nuclear engineering as the speaker presents research on developing efficient sensing networks and predictive models for complex nuclear energy applications. Gain insights into how sparse sensing methodologies can reduce computational costs while maintaining system performance and safety in nuclear energy contexts.