Biography and education
Dr. Klepetko graduated from Texas A&M with a B.S. in Computer Scienence in May 1990. Since he has worked in the Broadcast, Utility, and Web Development industries. In 1997 he returned to academia to reinforce his knowledge of Security and Artificial Intelligence and received his PhD in Electrical Engineering in December of 2022.
Featured scholarly/creative works
- Holiday, G., & Klepetko, R. S. (2025). Interpreting CNN in Cybersecurity: Process-Level Attribution via Benign-Replacement Occlusion (BRO). IEEE. https://doi.org/10.1109/ICCST63435.2025.11295312
- Klepetko, R. S., & Krishnan, R. (2023). Micam: Visualizing Feature Extraction of Nonnatural Data. In 4th International Conference on Machine Learning and Soft Computing (pp. 01–19). https://doi.org/10.5121/csit.2023.130201
- Klepetko, R. S., & Krishnan, R. (2022). Visualizing Convolutional Neural Network Models’ Sensitivity to Nonnatural Data Order. Information Systems Frontiers, 25(2), 613–638. https://doi.org/10.1007/s10796-022-10330-0
- Klepetko, R. S., & Krishnan, R. (2021). Analyzing CNN Models’ Sensitivity to the Ordering of Non-natural Data. In R. Krishnan, H. R. Rao, S. K. Sahay, S. Samtani, & Z. Zhao (Eds.), Secure Knowledge Management In The Artificial Intelligence Era - 9th International Conference, SKM 2021, San Antonio, TX, USA, October 8-9, 2021, Proceedings (Vol. 1549, pp. 130–148). Springer. https://doi.org/10.1007/978-3-030-97532-6\_8
- Klepetko, R. S., & Krishnan, R. (2019). Analyzing CNN Model Performance Sensitivity to the Ordering of Non-Natural Data. In 2019 4th International Conference on Computing, Communications and Security (ICCCS), Rome, Italy, October 10-12, 2019 (pp. 1--8). IEEE. https://doi.org/10.1109/CCCS.2019.8888041
Featured service activities
- Undergraduate Advisor
Cyber Security Club
- Undergraduate Advisor
KTSW
- Undergraduate Advisor
Coop Program
- Undergraduate Advisor
Boko Hacks