{"id":47,"date":"2025-11-19T14:28:14","date_gmt":"2025-11-19T14:28:14","guid":{"rendered":"https:\/\/sciences.ncsu.edu\/ai\/?page_id=47"},"modified":"2026-09-24T16:00:15","modified_gmt":"2026-09-24T20:00:15","slug":"research","status":"publish","type":"page","link":"https:\/\/sciences.ncsu.edu\/ai\/research\/","title":{"rendered":"Research"},"content":{"rendered":"\n\n\n\n\n
\"Artist's<\/figure>\n\n\n\n

Faculty at NC State are deeply engaged in AI-related research. The table below shows AI-related research projects led by College of Sciences faculty<\/strong>.<\/p>\n\n\n

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Project Title<\/th>Funding Agency<\/th>Department<\/th>PI List<\/th>Fiscal Year(s)<\/th><\/tr>\n<\/thead>\n
AI Institute: Artificial Intelligence for Environmental Sciences (AI2ES)<\/td>NSF-University of Oklahoma<\/td>MEAS<\/td>He, Ruoying (lead); Liu, Paul<\/td>2022, 2023, 2024, 2025, 2026<\/td> <\/tr>\n
CCI Phase I: NSF Center for Accelerated Photocatalysis (CAPs)<\/td>National Science Foundation (NSF)<\/td>Chemistry<\/td>Castellano, Felix (lead); Abolhasani, Milad; Pierce, Joshua; Williams Cherry, Tova<\/td>2025<\/td> <\/tr>\n
Collaborative Research: CAIG: Multi-Architecture Physics-Informed Deep Leaning for Understanding Coastal Hypoxia Formation Mechanisms<\/td>National Science Foundation (NSF)<\/td>MEAS<\/td>Liu, Paul (lead); He, Ruoying; Xu, Dongkuan<\/td>2027<\/td> <\/tr>\n
Hidden Markov Methodology for Machine Learning Applied to Identifying Physiological States Of Shock in the Intensive Care Unit Via Biomedical and Unstructured Text Data<\/td>National Institutes of Health (NIH)<\/td>Statistics<\/td>Williams, Jonathan (lead); Reich, Brian<\/td>2022, 2023<\/td> <\/tr>\n
Transforming Clinical Trials for Elderly and Rare Cancers through Intelligent and Robust Information Borrowing<\/td>National Institutes of Health (NIH)<\/td>Statistics<\/td>Yang, Shu (lead)<\/td>2027<\/td> <\/tr>\n
CIF: Small: Signal Recovery Beyond Minimization: A Monotone Inclusion Framework<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Combettes, Patrick (lead)<\/td>2022, 2025<\/td> <\/tr>\n
A Gut-brain Interaction Controlling Reward Learning<\/td>Virginia Polytechnic Institute and State University<\/td>Statistics<\/td>Sengupta, Srijan (lead)<\/td>2023, 2024, 2025, 2026, 2027<\/td> <\/tr>\n
Quantum Utility with Hardware- and Application- Informed Near-Term Algorithms (QUINTA)<\/td>Virginia Polytechnic Institute and State University<\/td>Research<\/td>Kemper, Lex (lead)<\/td>2025, 2026<\/td> <\/tr>\n
Atmospheric River Program Phase V<\/td>University of California - San Diego<\/td>MEAS<\/td>Lackmann, Gary (lead); Michaelis, Allison (lead); Lackmann, Gary; Michaelis, Allison<\/td>2025, 2026<\/td> <\/tr>\n
DMREF: Collaborative Research: AI-Driven Design of Tough 2D Metal Halide Perovskites for Next-Generation Semiconductor Applications<\/td>National Science Foundation (NSF)<\/td>Chemistry<\/td>Li, Xiaotong (lead)<\/td>2027<\/td> <\/tr>\n
A Geometric Framework for Stochastic Algorithms in Feasibility and Inclusion Problems<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Combettes, Patrick (lead)<\/td>2025<\/td> <\/tr>\n
EMN-21-F-S-01 Predict Diverse System Solubility<\/td>Eastman Chemical Company<\/td>Statistics<\/td>Hughes-Oliver, Jacqueline (lead); Baynes, Ronald; Santiso, Erik<\/td>2022, 2023<\/td> <\/tr>\n
AI Water Guardians: Empowering North Carolina Communities to Monitor and Predict Harmful Algal Blooms in Falls Lake Using Artificial Intelligence<\/td>US Environmental Protection Agency (EPA)<\/td>MEAS<\/td>Liu, Paul (lead); Painter, Jason; Shelton, Taryn<\/td>2027<\/td> <\/tr>\n
Development of RMG Code Nanoscale Applications<\/td>UT-Battelle, LLC dba Oak Ridge National Laboratory<\/td>Physics and Astronomy<\/td>Bernholc, Jerzy (lead); Briggs, Emil; Lu, Wenchang<\/td>2025, 2026<\/td> <\/tr>\n
Multi-task Biologically Informed Neural Networks For Learning Dynamical Systems From Single-cell Protein Expression Data<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Flores, Kevin (lead); Arguello-Miranda, Orlando<\/td>2025, 2026<\/td> <\/tr>\n
Effective Computational Methods for Training of Neural Networks via Exploration-Exploitation-Determination Framework<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Shin, Yeonjong (lead)<\/td>2025, 2026<\/td> <\/tr>\n
Algorithms, Theory, and Applications for Fiber Coating Systems<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Ji, Hangjie (lead)<\/td>2023, 2026<\/td> <\/tr>\n
Preparing the Next Generation of Biostatisticians in the Era of Data and Translational Sciences<\/td>National Institutes of Health (NIH)<\/td>Statistics<\/td>Ghosh, Sujit (lead); McGowan, Herle<\/td>2022, 2023, 2024<\/td> <\/tr>\n
Atmospheric River Program Phase V<\/td>University of California - San Diego<\/td>MEAS<\/td>Lackmann, Gary (lead); Michaelis, Allison (lead); Lackmann, Gary; Michaelis, Allison<\/td>2026, 2027<\/td> <\/tr>\n
PARTNER: An AI\/ML Collaborative for Southeast Florida Coastal Environmental Data and Modeling Center<\/td>Florida International University<\/td>MEAS<\/td>He, Ruoying (lead)<\/td>2024, 2025, 2027<\/td> <\/tr>\n
Structure and Statistics of Disordered Systems<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Bates, Erik (lead)<\/td>2024, 2026<\/td> <\/tr>\n
Electron-Deficient Conjugated Polymers with Prototypical Bond Topologies<\/td>US Dept. of Energy (DOE)<\/td>Chemistry<\/td>Chiechi, Ryan (lead)<\/td>2026<\/td> <\/tr>\n
Increased Deep Learning Computing Capacity for Radar Applications<\/td>US Air Force Office of Scientific Research (AFOSR)<\/td>Mathematics<\/td>Tsynkov, Semyon (lead)<\/td>2023, 2024<\/td> <\/tr>\n
AEROFUSION-MLUQ: Mars Lander Aerodynamic Model Data Fusion using Machine Learning with Embedded Uncertainty Quantification<\/td>National Aeronautics & Space Administration (NASA)<\/td>Mathematics<\/td>Smith, Ralph (lead)<\/td>2022, 2023<\/td> <\/tr>\n
Nonlinearity and Information Processing<\/td>US Navy - Office Of Naval Research<\/td>Physics and Astronomy<\/td>Ditto, William (lead)<\/td>2022, 2023, 2024<\/td> <\/tr>\n
Causal Inference with Irregularly-spaced Observation Times<\/td>National Science Foundation (NSF)<\/td>Statistics<\/td>Yang, Shu (lead)<\/td>2024, 2026<\/td> <\/tr>\n
Collaborative Research: RUI: Density of Modes: A New Way to Forecast Sediment Failure<\/td>National Science Foundation (NSF)<\/td>Physics and Astronomy<\/td>Daniels, Karen (lead)<\/td>2023, 2026<\/td> <\/tr>\n
Offline Statistical Reinforcement Learning with Applications in Precision Health<\/td>National Science Foundation (NSF)<\/td>Statistics<\/td>Lu, Wenbin (lead)<\/td>2022, 2023, 2024, 2026<\/td> <\/tr>\n
Non-local Variational Problems with Applications to Data Science<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Murray, Ryan (lead)<\/td>2023, 2025, 2026<\/td> <\/tr>\n
Data-free Operator Learning for real-time turbulent CFD simulations in Air-Conditioning Applications<\/td>LG Electronics<\/td>Mathematics<\/td>Shin, Yeonjong (lead)<\/td>2026<\/td> <\/tr>\n
Collaborative Research: CyberTraining: Pilot: iVirus: Advancing AI-driven Viral Ecology through training in Cyberinfrastructure and High-Performance Computing<\/td>National Science Foundation (NSF)<\/td>Biological Sciences<\/td>Hurwitz, Bonnie (lead)<\/td>2026<\/td> <\/tr>\n
Deep Neural Networks for Solving Non-Markov Optimization Problems<\/td>National Science Foundation (NSF)<\/td>Mathematics<\/td>Papanicolaou, Andrew (lead)<\/td>2022, 2023, 2024<\/td> <\/tr>\n
NAMs-Decisions Center: New Approach Methods for Decisions on Industrial and Consumer-Use Chemicals<\/td>Texas A&M University<\/td>Statistics<\/td>Wright, Fred (lead)<\/td>2026<\/td> <\/tr>\n
STREAMLINE Collaboration: Machine Learning for Nuclear Many-Body Systems<\/td>US Dept. of Energy (DOE)<\/td>Physics and Astronomy<\/td>Koenig, Sebastian (lead)<\/td>2024, 2025, 2026<\/td> <\/tr>\n
Data-free Operator Learning via Physics-Informed Deep Operator Networks for Fast CFD Simulations in Home Appliance and Air-conditioning<\/td>LG Electronics<\/td>Mathematics<\/td>Shin, Yeonjong (lead)<\/td>2025<\/td> <\/tr>\n
PILOT-Wildfire Pollution Exposure and Human Health: Building a Novel AI-powered Air Quality Forecasting Model for a Growing Public Health Issue<\/td>NCSU Center for Human Health and the Environment<\/td>Statistics<\/td>Sengupta, Srijan (lead); Aneja, Viney<\/td>2022<\/td> <\/tr>\n
STREAMLINE 2 Collaboration: Machine Learning for Nuclear Many-Body Systems<\/td>Michigan State University<\/td>Physics and Astronomy<\/td>Koenig, Sebastian (lead)<\/td>2026<\/td> <\/tr>\n
Broadening Participation Research Project: Data Science and Machine Learning: An Interdisciplinary STEM Training for the Future Workforce<\/td>Benedict College<\/td>Mathematics<\/td>Medhin, Negash (lead)<\/td>2024, 2026<\/td> <\/tr>\n
A Novel Artificial Intelligence \/ Machine Learning Approach for High-efficiency, High-fidelity Marine Wave Energy Characterization and Assessment for Powering the Blue Economy<\/td>Fathom Science<\/td>MEAS<\/td>He, Ruoying (lead)<\/td>2024<\/td> <\/tr>\n
A Predictive Engine for Protein-Nucleic Acid Interactions in Therapeutic Aptamer Design<\/td>UNC\/NC State Translational Research Grant (NC TraCS)<\/td>Physics and Astronomy<\/td>Lin, Xingcheng (lead); GRA TBA,; Weninger, Keith; Xiao, Yi<\/td>2027<\/td> <\/tr>\n
Forecasting Anomalous Atlantic Hurricane Seasons Using Explainable AI, CARTA Core Project<\/td>Center for Accelerated Real Time Analytics (CARTA) - NCSU Research Site<\/td>MEAS<\/td>Xie, Lian (lead); Shen, Xipeng<\/td>2023, 2024<\/td> <\/tr>\n
Predicting Air Pollution in Disadvantaged Communities in the United States with Deep Learning<\/td>NC State Data Science Academy<\/td>MEAS<\/td>Qu, Zhen (lead); Boone, Kofi; Liu, Xiaorui<\/td>2023<\/td> <\/tr>\n
Collaborations in Applied Analysis<\/td>Simons Foundation<\/td>Mathematics<\/td>Murray, Ryan (lead)<\/td>2024<\/td> <\/tr>\n
PDE-Principled Data-Driven Learning Framework for Droplet Dynamics<\/td>Simons Foundation<\/td>Mathematics<\/td>Ji, Hangjie (lead)<\/td>2024<\/td> <\/tr>\n
Geometric Methods in Partial Differential Equations and Computer Vision<\/td>Simons Foundation<\/td>Mathematics<\/td>Kogan, Irina (lead)<\/td>2022, 2023, 2025<\/td> <\/tr>\n
Building LLM Agents for Large Environmental Dataset Analysis<\/td>NC State Data Science Academy<\/td>MEAS<\/td>Liu, Paul (lead); Cheng, Alice; Xu, Dongkuan<\/td>2025<\/td> <\/tr>\n
Visiting Joint Postdoctoral Associate Appointment of Dr. Andrey Tarasov<\/td>State University of New York at Stony Brook (SUNY)<\/td>Physics and Astronomy<\/td>Skokov, Vladimir (lead); Tarasov, Andrey<\/td>2025<\/td> <\/tr>\n
High Efficiency Gyrotron Technology<\/td>Calabazas Creek Research, Inc.<\/td>Mathematics<\/td>Tran, Hien (lead)<\/td>2024<\/td> <\/tr>\n
Unveiling the Connection Between Gas Flows Around Galaxies and the Cosmic Web Using Qso Spectra<\/td>Space Telescope Science Institute<\/td>Physics and Astronomy<\/td>Bordoloi, Rongmon (lead)<\/td>2024<\/td> <\/tr>\n
Aligning Student and Instructor Expectations with Large Language Models in Chemical Education<\/td>DELTA (Distance Education & Learning Technologies Applications, NCSU)<\/td>Chemistry<\/td>Chiechi, Ryan (lead); Feducia, Jeremiah<\/td>2026<\/td> <\/tr>\n
The new interviewer: Leveraging AI-driven data collection to identify instructor knowledge for teaching research<\/td>SimBio Foundation<\/td>Biological Sciences<\/td>Cooper, Lexie (lead); Undergraduate, Ugrad<\/td>2027<\/td> <\/tr>\n
Statistical Foundations for Uncertainty Quantification of Machine Intelligence Assembled from Generalized Fiducial Inference<\/td>NCSU Faculty Research & Professional Development Fund<\/td>Statistics<\/td>Williams, Jonathan (lead)<\/td>2025<\/td> <\/tr>\n
Data-driven Discovery of Multi-domain Models for Droplet Dynamics<\/td>NCSU Faculty Research & Professional Development Fund<\/td>Mathematics<\/td>Ji, Hangjie (lead)<\/td>2023<\/td> <\/tr>\n
Data Analysis, Non-smooth Optimization and Applications<\/td>NCSU Faculty Research & Professional Development Fund<\/td>Mathematics<\/td>Ito, Kazufumi (lead)<\/td>2023<\/td> <\/tr>\n
A Demonstration Of Real-time Analytics In Seasonal Hurricane Prediction, CARTA Core Project<\/td>Center for Accelerated Real Time Analytics (CARTA) - NCSU Research Site<\/td>MEAS<\/td>Xie, Lian (lead)<\/td>2022, 2023<\/td> <\/tr>\n
CAREER: Semiparametric and Machine Learning Approaches to Big Data Challenges in Precision Medicine<\/td>National Science Foundation (NSF)<\/td>Statistics<\/td>Song, Rui (lead)<\/td>2022<\/td> <\/tr>\n
Data-Driven Approaches to Identify Biomarkers for Guiding Coronary Artery Bifurcation Lesion Interventions from Patient-Specific Hemodynamic Models<\/td>Duke University<\/td>Statistics<\/td>Chi, Eric (lead)<\/td>2023<\/td> <\/tr>\n <\/tbody>\n <\/table>\n \n \n \n<\/div>\n\n\n\n\n

Video: Our AI Research<\/h2>\n\n\n\n

Learn more about some of our research in artificial intelligence through short videos produced by our faculty.<\/p>\n\n\n\n

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