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Bio

Dr. Xu Wu is an Associate Professor of Nuclear Engineering at North Carolina State University. Dr. Wu’s main research interests include: uncertain quantification, Bayesian inverse problems, model discrepancy analysis, scientific machine learning and deep generative modeling. Dr. Wu received his BS in Nuclear Engineering from Shanghai Jiao Tong University in 2011 and PhD in Nuclear Engineering from University of Illinois at Urbana – Champaign in 2017. Prior to joining NC State in 2019, he worked as a Postdoctoral Research Associate at the Department of Nuclear Science and Engineering at MIT.

Publications

• Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code , Nuclear Technology (2026)
• Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux , Energy and AI (2026)
• Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation , Nuclear Science and Engineering (2026)
• An investigation on machine learning predictive accuracy improvement and uncertainty reduction using VAE-based data augmentation , Nuclear Engineering and Design (2025)
• Bayesian Calibration and Sensitivity Analysis of Rayleigh Scattering Fiber Optic Distributed Temperature Sensing in Water Flow Loop , Nuclear Science and Engineering (2025)
• Data-driven prediction and uncertainty quantification of PWR crud-induced power shift using convolutional neural networks , Energy (2025)
• Monte Carlo Dropout Uncertainty Quantification of Long Short-Term Memory Autoencoder Anomaly Detection in a Liquid Sodium Cold Trap , Nuclear Technology (2025)
• Physics-based hybrid machine learning for critical heat flux prediction with uncertainty quantification , Applied Thermal Engineering (2025)
• Predicting critical heat flux with uncertainty quantification and domain generalization using conditional variational autoencoders and deep neural networks , Annals of Nuclear Energy (2025)
• Sensitivity and uncertainty analysis in pebble-bed reactors: A study using the High-Temperature Code Package (HCP) , Annals of Nuclear Energy (2025)

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