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The research in the ARTISANS group revolves around uncertainty quantification (UQ) and scientific machine learning (SciML). The goal is to combine SciML, experimentation and modeling & simulation (M&S) into a unified approach to improve the predictive capabilities of computer models and enable reduced reliance on expensive measurement data. Additionally, the application of such research will be focused on risk and economics evaluations of advanced nuclear reactors, such as small modular reactors and micro-reactors. The ultimate goal is to dramatically reduce the capital and operating costs of nuclear systems to maintain global technology leadership for nuclear energy.
Our main research interests include: (1) calibration, validation, data assimilation, uncertainty and sensitivity analysis; (2) computational statistics, reduced order modeling; (3) Bayesian inverse problems; (4) scientific machine learning and deep generative learning; (5) system thermal-hydraulics, nuclear fuel performance modeling, multi-physics coupled simulation; (6) advanced reactors, small modular reactors, micro-reactors.
Recent News
- Jaden receives the ANS RPD Massimo Salvatores Memoriam Graduate ScholarshipCongratulations to Jaden for being selected as a recipient of the 2026-2027 American Nuclear Society (ANS) Reactor Physics Division (RPD) Massimo Salvatores Memoriam Graduate Scholarship.
- Aidan successfully defended his PhD thesisCongratulations to Aidan for successfully defending his PhD thesis titled “Development, Refinement, and Deployment of Explainable and Interpretable Critical Heat Flux Machine Learning Models”.
- New grant from DOE Nuclear Energy University Program (NEUP)The ARTISANS group has been awarded a new Nuclear Energy University Program (NEUP) project from U.S. Department of Energy (DOE). We will receive $1 million…
- Farah and Alie’s journal paper accepted by Energy and AIFarah and Alie’s paper titled “Development of Physics-consistent Conditional Diffusion Model to Overcome Data Scarcity in Critical Heat Flux” has been accepted by Energy and…
- Alie receives the John T. McCarter Jr. FellowshipCongratulations to Alie for being selected to receive the John T. McCarter Jr. Graduate Student Fellowship from the NC State Department of Nuclear Engineering.
- CORA proposal selected by the NCSU Dean’s COE Applied AI Research Accelerator AwardOur proposal titled “Foundations for CORA (Cognitive Operator Readiness Assistant): Knowledge Graph and Prototype Large Language Model for Nuclear Operator Training” has been selected by…
- Jason’s paper selected as an Editor’s Choice Article in WEVJJason’s paper titled “Understanding EV Charging Pain Points Through Deep Learning Analysis” has been selected as an Editor’s Choice Article in World Electric Vehicle Journal…
- Aidan’s journal article accepted by Nuclear TechnologyAidan’s journal paper “Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal Hydraulics Code” has been accepted by…
- Chris passed his PhD Prelim ExamCongratulations to Chris for passing his PhD Prelim Exam with the title “Nuclear Data Adjustment with Bayesian Inverse UQ for Radiation Transport Simulations in Nuclear…