Ericmoore Jossou

Ericmoore Jossou holds the John Clark Hardwick (1986) Professorship and is an Assistant Professor of Nuclear Science and Engineering and Electrical Engineering and Computer Science at MIT. His research focuses on advancing materials for next-generation nuclear reactors through integrated experimental, computational, and data-science approaches. Key areas include high-throughput machine learning for nuclear fuel design, in situ monitoring of materials under irradiation, and atomic-scale simulations of radiation effects.

• Leads efforts to develop accident-tolerant fuels and high-entropy alloys using novel synthesis and characterization techniques.
• Develops multimodal imaging tools for real-time material analysis, including 3D X-ray tomography and Bragg coherent diffraction.
• Explores machine learning applications in materials discovery, phase prediction, and high-speed video segmentation.

His work addresses critical challenges in nuclear energy sustainability, such as improving fuel performance under extreme conditions and enhancing materials durability for advanced reactor systems. Recent contributions include studies on uranium-doped fuel microstructures, strain relaxation mechanisms, and thermal conductivity optimization of composite materials.

Research outputs span computational modeling, experimental validation, and data-driven methodologies, with a focus on bridging atomic-scale mechanisms to macroscopic material behavior.