Dr. Temechu Girma Zewdie is an Assistant Professor of Computer Science and Engineering at the University of the District of Columbia’s School of Engineering and Applied Sciences. His expertise spans cybersecurity, artificial intelligence, cloud computing, IoT security, and machine learning. Dr. Zewdie has published extensively on topics such as ransomware detection, malware identification in cyber-physical systems, and securing software-defined networks.
Experience
Education
Doctor of Philosophy in Computer Science and Engineering, University of the District of Columbia Master of Science in Cybersecurity & Information Assurance, Virginia Institute of Science & Technology Master of Science in Software Engineering, HiLCoE School of Computer Science and Technology Master of Business Administration in Management, University of Nicosia Bachelor of Science in Computer Science, HiLCoE School of Computer Science and Technology
Roles
Assistant Professor, Computer Science and Engineering, UDC, 2023-Present
Courses Taught
Database Administration IT System Component Security Data Communication and IP Management Introduction to Programming with Python (Lecture) Introduction to Programming with Python (Lab) Computer Science I (C++) Lecture Computer Science I (C++) Lab Foundations of Computing
Expertise
Research Focus / Works in Progress
KCybersecurity and information assurance; IoT; artificial intelligence; cloud computing and security; IoT analytics and security; database; software engineering
Impact
Selected Publications
Zewdie, T.G., Girma, A., & Cotae, P. (2022). Ransomware attack detection on the internet of things using machine learning algorithm. In J.Y.C. Chen, G. Fragomeni, H. Degen, & S. Ntoa (Eds.), HCI International 2022 – Late breaking papers: Interacting with eXtended reality and artificial intelligence (Lecture notes in computer science).Springer.
Zewdie, T.G., Girma, A., & Cotae, P. (2022). Malware detection framework in cyber-physical systems using artificial intelligence - Machine learning. Issues in Information Systems, 23(1), 316-332. https://doi.org/10.48009/1_iis_2022_126
Zewdie, T.G., & Girma, A. (2022). An evaluation framework for machine learning methods in detection of DoS and DDoS intrusion. In Proceedings of the 2022 International Conference on Artificial Intelligence in Information and Communication.https://doi.org/10.1109/ICAIIC54071.2022.9722661
Zewdie, T.G., & Girma, A. (2022). Securing software defining network from emerging DDoS attack. In A. Moallem (Ed.), HCI for cybersecurity, privacy, and trust. Springer.
Zewdie, T.G., & Girma, A. (2020). IoT security and the role of AI/ML to combat emerging cyber threats in cloud computing environment. Information Systems Journal. 21. 253-263. https://doi.org/10.48009/4_iis_2020_253-263.
Zewdie, T.G. (2020). Usable security case of remote web access. In C. Stephanidis, M. Antona, & S. Ntoa (Eds.), HCI International 2020 – Late breaking posters.Springer.
Selected Presentations
Zewdie, T.G., & Girma, A. (2020). Cybersecurity in industrial robotics.Workshop at the Robotics: Science and Systems Conference, Virtual.
