SMART Lab PhD student Zavier Ndum has been selected as a Texas A&M Chevron Energy Graduate Fellow for his innovative research on applying GenAI and digital twin technology to Nuclear Engineering Applications: https://energy.tamu.edu/news_item/announcing-the-2025-2026-texas-am-chevron-energy-graduate-fellows/
Congratulations to Zavier!
In the 2025 ANS Annual Meeting, Dr. Liu served as a panelist in the “Thermal Hydraulic Education: Opportunities with AI” panel, where he discussed his experience and SMART group’s ongoing on how AI tools are being used in the classroom and in research. Dr. Liu also presented the work “Advancing Nuclear R&D with GenAI: Case Studies in Thermal Hydraulics, Simulation Workflows, and Education” which summarizes several ongoing researches on GenAI and LLM agents in SMART Group.
SMART group student Zavier Ndum presented his research work on “Development and Demonstration of an AI-Assisted Digital Twin Framework for Remote Monitoring and Control of Advanced Small-Scale Reactors”.
SMART group student Zaid Abulawi presented his research work on “Multiphysics Coupled Calculations Using OpenFOAM, Serpent, and External Heat Conduction Solver for Prismatic GCRs: A Case Study on HTTR”.
SMART group students Zaid Abulawi and Zavier Ndum started their summer internship at ANL in May. They will work with Argonne researchers in the Nuclear Science and Engineering Division to integrate GenAI and AI Agents to support advanced nuclear reactor safety analysis and modeling.
Texas A&M Hosted Inaugural AI Workshop for Science and Engineering in May. (https://engineering.tamu.edu/news/2025/06/texas-am-hosts-inaugural-ai-workshop-for-science-and-engineering.html)
Dr. Liu served as a panelist on the “AI Agents for Science and Engineering”, where he discussed the recent advancements in SMART group on using GenAI and LLM agents for various nuclear engineering applications.
Zavier, as a TAMIDS Student Ambassador, gave a presentation at the “Generative AI Mastery: From Theory to Practice“ workshop on October 12, 2024. The event, hosted by TAMIDS with collaborators from NASA, Prairie View A&M, and Texas Southern University, focused on cutting-edge AI models and their applications.
“My work on integrating Monte Carlo methods with generative AI for optimizing radiation detection systems automating Modelling and Simulation Software for advanced nuclear reactor technologies garnered valuable feedback, helping me refine my models and gain deeper insights into state-of-the-art advancements in the field”.
Zavier delivered a seminar titled “Large Language Models (LLMs) and AI Agents Applications in Nuclear Science and Engineering” at the RAISE AI Lunch Seminar on October 30, 2024. The presentation highlighted the transformative role of AI and LLMs in automating and optimizing Monte Carlo simulations and nuclear engineering workflows. Zavier’s insights showcased how AI-driven tools enhance predictive capabilities, improve decision-making, and streamline complex engineering processes, offering innovative solutions for greater efficiency and productivity in the field.
Zavier presented his paper titled “A Digital Twin-Based Simulator for Small Modular and Microreactors” at the IEEE Winter Simulation Conference (WSC 2024) in Orlando, Florida. As part of the PhD colloquium, Zavier delivered a 7-minute presentation of his thesis idea, participated in a poster session, and conducted a 30-minute full paper presentation.
“This conference offered me a unique opportunity and a platform to network with professionals across different disciplines, providing invaluable feedback and insights that will help me to refine and advance my PhD research”.
Zavier delivered a talk titled “Generative AI as a Virtual Assistant to Health Physicists” at the STC-HPS Fall Conference held in Arlington, Texas, from October 2-4, 2024. The presentation showcased how Retrieval-Augmented Generation (RAG) can serve as a personalized assistant and recommender system for Health Physicists, Radiation Safety Officers (RSOs), and Regulators in the Field. By leveraging RAG’s dynamic and context-aware capabilities, Zavier highlighted innovative solutions for improving decision-making, knowledge management, and operational efficiency in radiation safety, positioning AI as an essential tool in modern health physics practices.
Zaid presented his work “Eddy Viscosity Prediction and Uncertainty Quantification with Bayesian Optimized Deep Ensemble” at the ANS Advances in Thermal Hydraulics (ATH 2024) conference.
The journal version of this work is currently under review.
Congratulations Zaid!
Dr. Yang Liu attended The 14th International Topical Meeting on Nuclear Reactor Thermal-Hydraulics, Operation, and Safety(NUTHOS-14) in Vancouver, Canada on August 25-28. He chaired a panel which discussed the progress, challenges, and opportunities on applying AI/ML for nuclear thermal hydraulics. He also presented a research paper “Development of data-driven eddy viscosity closure to support MSR flow and heat transfer modeling based on SAM-ML”.
