HNRS 3025/3035: Large Language Model (LLM) Development and Deployment for Real-World Applications
Artificial Intelligence
Cybersecurity
AI Security
Machine Learning
Neural Network Architecture
Neuromorphic Computing
Nuclear roliferation detection
Walton, B. J., Khatun, M. E., Ghawaly, J. M., & Ali-Gombe, A. (2025). Exploring Large
Language Models for Semantic Analysis and Categorization of Android Malware. arXiv
preprint arXiv:2501.04848.
Ghawaly, J., Nicholson, A. D., Schuman, C. D., Swinney, M., Witherspoon, B., Young,
A., ... & Prins, N. (2024). OR22-Neuromorphic Rad Detector-PD3Ra (No. ORNL/SPR-2024/3423).
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States).
Peplow, D. E., Archer, D. E., Nicholson, A. D., Prins, N. J., Bandstra, M. S., Jones,
A. C., ... & Ghawaly Jr, J. M. (2024). Threat Sources for Creating Synthetic Urban
Search Data (No. ORNL/TM-2024/3265). Oak Ridge National Laboratory (ORNL), Oak Ridge,
TN (United States).
Bandstra, M. S., Britt, C., Ghawaly, J., Grimes, T., Haard, T., Heimberg, P., ...
& Thoreson, G. (2024). Metrics and Methods for Radiation Detection Algorithm Characterization
for Nuclear/Radiological Source Search (No. ORNL/TM-2023/2906). Oak Ridge National
Laboratory (ORNL), Oak Ridge, TN (United States).
Bandstra, M. S., Curtis, J. C., Ghawaly Jr, J. M., Jones, A. C., & Joshi, T. H. (2023).
Explaining machine-learning models for gamma-ray detection and identification. Plos
one, 18(6), e0286829.
Ghawaly, J., Young, A., Nicholson, A., Witherspoon, B., Prins, N., Swinney, M., ...
& Patel, K. (2023, August). Performance Optimization Study of the Neuromorphic Radiation
Anomaly Detector. In Proceedings of the 2023 International Conference on Neuromorphic
Systems (pp. 1-7).
Ghawaly Jr, J. M., Nicholson, A. D., Archer, D. E., Willis, M. J., Garishvili, I.,
Longmire, B., ... & Cook, M. T. (2022). Characterization of the autoencoder radiation
anomaly detection (arad) model. Engineering Applications of Artificial Intelligence,
111, 104761.
Ghawaly, J., Young, A., Archer, D., Prins, N., Witherspoon, B., & Schuman, C. (2022,
July). A neuromorphic algorithm for radiation anomaly detection. In Proceedings of
the International Conference on Neuromorphic Systems 2022 (pp. 1-6).
Biegalski, S. R., Tsvetkov, P. V., Tao, Y., Sobes, V., Pazdernik, K., Labov, S., ...
& Williams, D. F. (2021, July). 2020 ETI Annual Summer School: Data Science and Engineering.
In 2021 ASEE Virtual Annual Conference Content Access.
Ghawaly, J. M., Nicholson, A. D., Peplow, D. E., Anderson-Cook, C. M., Myers, K. L.,
Archer, D. E., ... & Quiter, B. J. (2020). Data for training and testing radiation
detection algorithms in an urban environment. Scientific data, 7(1), 1-6.
2025: Source: DOE, Title: DNN's Enabling Capabilities in Technology Consortium, LSU
PI: James Ghawaly, $750,000.
2024: Source: NPS, Title: Enhancing Historic Preservation Through Partnership to Create
Machine Learning Models, Co-I: James Ghawaly, $250,000.
2023: Source: DOE, Title: Compact Radiation Arrays for Tracking and Interdiction,
PI: James Ghawaly, $678,000.
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