Assistant Professor
School of Engineering and Computing, Christopher Newport University
Email: yan.lu@cnu.edu
Phone: (757) 594-7626
Address: Luter Hall, Room 325, Newport News, VA 23606
Webpage: https://cnu.edu/people/yanlu/
Google Scholar: https://scholar.google.com/citations?user=0PQ0X6IAAAAJ&hl=en
Dr. Yan Lu is an Assistant Professor of Computer Science in the School of Computing and Engineering at Christopher Newport University, where she joined in Fall 2023. Prior to her appointment at CNU, she served as a Research Assistant Professor at the Virginia Modeling Analysis and Simulation Center at Old Dominion University and Research Scientist at the Virginia Commonwealth Cyber Initiative. Dr. Lu earned her Ph.D. in Computational Modeling and Simulation Engineering from Old Dominion University in 2020, an M.Sc. in Computer Science from Virginia Commonwealth University in 2009, an M.Sc. in Circuit and System from the Chinese Academy of Sciences in 2007, and a B.A. in Computer Science from Beijing Jiaotong University in 2004.
Dr. Yan Lu's current research primarily focuses on Deep Learning, Machine Learning, Artificial Intelligence and their applications in Remote Sensing Image Processing and Trustworthy AI. She is an active member of prestigious professional organizations including IEEE and ACM, as well as its Special Interest Group onSimulation (SIGSIM). In 2019, Dr. Lu received the Gene Newman Award for Excellence in Modeling and Simulation Research from Old Dominion University. Her work on Deep Learning for Effective Refugee Tent Extraction using Satellite Images was featured in the world-leading engineering magazine, IEEE Spectrum in 2020. Dr. Lu was honored with the Summer Visiting Faculty Research Program (VFRP) awards from the Air Force Research Lab InformationDirectorate in Rome, New York starting from 2020. This recognition further highlights her contributions to the field of research and academia.
1. Brennan Miller, Abdul Abouti, Erika.Ardiles-Cruz, Yan Lu, “Physics-Informed Deep Learning with GLCM-Integrated Loss for Building Damage Assessment Using Remote Sensing”, IEEE 26th International Conference on Information Reuse and Integration for Data Science, Aug 6-8, 2025, San Jose, CA
2. Shen, Yuying, Lu, Yan, Turner, Carlene, & Turner, Claude. “Cyberbullying Victimization among Adolescents: Machine Learning Analysis of Survey Data.” 2025 39th International RAIS Conference on Social Science & Humanities, April 17 – 18, Princeton University, NJ
3. Yuying Shen, Yan Lu, Carlene Turner, Claude Turner, Cyberbullying Victimization among Adolescents: Machine Learning Analysis of Survey Data , RAIS Journal for Social Sciences: Vol. 9 No. 1 (2025): RAIS Journal for Social Sciences
4. Yan Lu, Jiang Li, “RS-ScaleGAN: a hierarchical multi-scale gan network for data augmentation in remote sensing”, 2025 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2025)
5. Yan Lu, Joshua Prinzel, Mason Beckmeyer, Erika.Ardiles-Cruz, “Fast and Few: Prototypical Networks for Real-Time Post-Disaster Damage Assessment in Disaster Zones,” Accepted for Oral presentation by SPIE Artificial Intelligence and Image and Signal Processing for Remote Sensing XXXI conference
6. N. A. Nipa, Y. Lu and S. Shetty, "U-Net Based Disaster Damage Detection Through Semantic Segmentation," 2023 International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar, 2023.
7. L. Yan, Erika Ardiles-Cruz, " Physics-informed Deep Learning for Building Damage Assessment Using Remote Sensing Imagery ", Technique Report, Air Force Research Lab, Rome, NY, Aug 2023.
8. L. Kang, Rafael. Diaz, Y. Lu. "A Data-Driven Cyber Physical Security Vulnerability Assessment System for Autonomous Driving in Port Networks" IEEE Transactions on Intelligent Transportation System, under review, 2023.
9. L. Yan, Erika Ardiles-Cruz, “Learning a Hierarchical Multi-Scale Generative Adversarial Network for Building Damage Estimation and Disaster Recovery using Remote Sensing Images”, Technique Report, Air Force Research Lab, Rome, NY, Aug. 2022.
10. L. Yan, Sachin Shetty, “Towards AI Robustness Multi-Agent Adversarial Planning in Chinese Checker”, Winter Simulation Conference, Dec. 2022.
11. L. Yan, Benjamin Ritz. “Towards AI Robustness Multi-Agent Adversarial Planning in Game Play”, Technique Report, Air Force Research Lab, Rome, NY, Aug. 2021.
12. L. Yan and Sachin Shetty. "Multi-Class Malware Classification Using Deep Residual Network with Non-SoftMax Classifier," In proceedings of 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science, Aug. 10-12, 2021, Virtual Conference.
13. L. Yan, Koperski K, Kwan C, Li J. Deep Learning for Effective Refugee Tent Extraction Near Syria-Jordan Border. IEEE Geoscience and Remote Sensing Letters. Jun 24, 2020. (Reported in IEEE Spectrum:https://spectrum.ieee.org/new-ai-estimates-the-size-of-remote-refugee-camps-using-satellite-data )
14. Ayhan, B., Kwan, C., Budavari, B., Kwan, L., Y. Lu., Perez, D., Li, J., Skarlatos, D., and Vlachos, M., 2020. Vegetation Detection Using Deep Learning and Conventional Methods. Remote Sensing, 12(15), p.2502.
15. Kwan, C., Ayhan, B., Budavari, B., Y. Lu., Perez, D., Li, J., Bernabe, S., and Plaza, A., 2020. Deep Learning for Land Cover Classification Using Only a Few Bands. Remote Sensing, 12(12), p.2000.
16. B. Roland, K. Islam, J. Li and Y. Lu. “Data Augmentation with Generative Models for Improved Malware Detection: A Comparative Study,” In IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference. New York, Oct. 2019.
17. L. Yan and J. Li. “Generative Adversarial Network for Improving Deep Learning Based Malware Classification,” Winter Simulation Conference, 2019.
18. L. Yan, J. Graham, and J. Li. “Deep Learning Based Malware Classification Using Deep Residual Network.” In Proceedings of the 2019 Modeling, Simulation and Visualization Student Capstone Conference, Suffolk, Virginia, Apr 18, 2019. (Gene Newman Award)
19. L. Yan, D. Perez, M. Dao, C. Kwan, and J. Li. "Deep learning with synthetic hyperspectral images for improved soil detection in multispectral imagery." In Proceedings of the IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference, New York, NY, USA, pp. 8-10. 2018.
20. P. Daniel, Y. Lu, C. Kwan, Y. Shen, K. Koperski, and J. Li. "Combining satellite images with feature indices for improved change detection." In IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference. 2018.
21. M. Bharat and Y. Lu. "Attack tolerant big data file system." ACM Sigmetrics Big Data Analytics Workshop. 2013.
22. L. Huaxiang, Y. Lu, Z. Tang, S. Wang. “Research on System-Level Dynamic Power Management Using Learning Neural Networks,” The 2006 International Conference on Artificial Intelligence Proceedings, June 26-29, 2006, Las Vegas, US.
23. L. Huaxiang, Y. Lu, Z. Tang and S. Wang. “SOC Dynamic Power Management Using Artificial Neural Network,” Lecture Notes in Computer Science, Pages 555-564, Volume 4221/2006.
Faculty Development Grant 2024-2025 "Undergraduate Research in Deep Learning for Remote Sensing and AI-Based Computer Vision", 2024, Award amount: $3,800. Role: PI
Commonwealth Cyber Initiative CATAPULT Awards: "Generative Adversarial Network for Deep Learning-based Malware Detection Intellectual Property (IP) and Commercialization", 2023, Award amount: $50,000. Role: PI
HRBRC collaboration Accelerator Fund, "Social Estrangement and Virtual Connectivity of Children in COVID Era", 2023-2025, Award amount, $125,000. Role: Co-PI
Visiting Faculty Research Program Award at Air Force Research Lab, "Physics-informed image processing for battlefield building damage image processing", Summer 2023, Award amount: $18,757. Role: PI
Visiting Faculty Research Program Award at Air Force Research Lab, " Learning a Hierarchical Multi-Scale Generative Adversarial Network for Building Damage Estimation and Disaster Recovery using Remote Sensing Images ", Summer 2022, Award amount: $22,464. Role: PI
Visiting Faculty Research Program Award at Air Force Research Lab," Towards AI Robustness Multi-Agent Adversarial Planning in Game Play ", Summer 2021, Award amount: $17,922. Role: PI
Visiting Faculty Research Program Extension Award, Fall 2022, Award amount: $10,000. Role: PI
Visiting Faculty Research Program Extension Award, Fall 2021, Award amount: $10,000. Role: PI
Commonwealth Cyber Initiative, "CCI: Commonwealth Cyber Initiative: Building Bridges between CCI and the Arts and Design Communities: MovingChoreography to a New Universe: an AI-Driven Privacy Automation Approach", 2020. Amount: $25,000. Role: Co-PI
Lecture: CPSC 555 Machine Learning I, (2024/2025), CNU
Lecture: CPSC 250 Data Manipulation in Python, (2024/2025), CNU
Lecture: CPSC 150 Introduction to Programming in Python, (2023/2024), CNU
Lecture: ECE 419/519 (Spring 2023) Cyber Physical System Security, ODU.
Lecture: ECE 304 (Fall 2022) Probability, Statistics, and Reliability, ODU.
Mentor: CCI Undergraduate Cybersecurity Research Program (2020-2025), ODU.
Mentor: IA-REDI COE Cybersecurity Summer Internship (2016/ 2018), NSU.
Mentor: GENCYBER Summer Camp (July 2016), NSU.
Mentor: Memory and Malware Forensics by using FREDC, IAREDI, 2016-2019, NSU.
Teaching Assistant: CMSC 508. Database Theory, Dept. of Computer Science, VCU.
Teaching Assistant: CMSC 401 Algorithm Analysis with Advanced Data Structures, Dept. of Computer Science, VCU.
Mentored Student Projects
1. Cooper Bowden, Yan Lu, Anton Riedl, “Educating Citizens through Open-source RAG Chatbots: a Generative AI Approach” CCI symposium, Richmond, VA, April 14-15, 2025
2. Alyssa Caroll, Yan Lu, "Securing Biometric Data", CCI Undergraduate Research Report, ODU Digital Commons, COVA CCI, Spring 2025.
3. Felix Lov and Y. Lu "The Vulnerabilities of Artificial Intelligence Models and Potential Defenses", CCI Undergraduate Research Report, ODU Digital Commons, COVA CCI, Spring 2024.
4. Piper Hall and Y. Lu, "The Propagation and Execution of Malware in Images", CCI Undergraduate Research report, ODU Digital Commons, COVA CCI, Fall, 2023.