Niroop Sugunaraj
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Part-time Instructional, SEECS
- I use AI and machine learning to help critical infrastructure notice when something isn't behaving the way it should. My expertise is in unsupervised deep learning methods - specfically deterministic and probabilistic autoencoders - for anomaly detection.
Contact Info
- Email: niroop.sugunaraj@UND.edu
- Office: 701.777.4331
Office Address
SEECS
Upson II Room 366
243 Centennial Dr Stop 7165
Grand Forks, ND 58202-7165
Biography
Dr. Sugunaraj earned his Ph.D. in Electrical Engineering in 2026 from the University of North Dakota. His research advances data-driven machine-learning solutions to secure the bulk power grid, building on prior work in automotive and unmanned aerial vehicle (UAV) security. His research has appeared in IEEE Communications Surveys & Tutorials, IEEE NAPS (conference), IEEE Sensors, IEEE Access, and MDPI.
He has taught and mentored undergraduate and graduate students from courses in the M.S. in Cyber Security and B.S. in Cyber Security programs at the University of North Dakota. He serves as a journal and conference manuscript reviewer for the following publishers: IEEE, MDPI, Elsevier, Oxford Academic, Springer, and Frontiers.
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CSCI 587 – Ethical Hacking.
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CSCI 487 – Penetration Testing.
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EE 740/675 – Intrusion Detection Algorithms.
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EE 611/672 – Emerging Threats and Defenses.
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CSCI 290 – Cyber-Security and Information Assurance.
- Doctor of Philosophy (Ph.D.) in Electrical Engineering - May 2026, University of North Dakota (UND).
- Master of Science (M.S.) in Electrical Engineering - Dec 2021, University of North Dakota (UND).
- Bachelor of Engineering (B.E.) in Computer Engineering (Honors) - April 2018, University of Wollongong in Dubai (UOWD).
- Cybersecurity
- Artificial Intelligence
- Human Factors
- Deep Learning
See the full list on my Scholar profile. These are a few selected publications:
- N. Sugunaraj et al., “Distributed Energy Resource Management System (DERMS) Cybersecurity Scenarios, Trends, and Potential Technologies: A Review,” IEEE Communications Surveys & Tutorials, 2026.
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N. Sugunaraj and P. Ranganathan, “An Autoencoder-based Solution to Detect Denial of Service Attack Variants,” in 2025 57th North American Power Symposium (NAPS), 2025, pp. 1–9.
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N. Sugunaraj and P. Ranganathan, “Applications for autoencoders in power systems,” in 2024 56th North American Power Symposium (NAPS), 2024, pp. 1–7.
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Z. El Mrabet, N. Sugunaraj, P. Ranganathan, and S. Abhyankar, “Random forest regressor-based approach for detecting fault location and duration in power systems,” Sensors, vol. 22, no. 2, p. 458, 2022.
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Z. El-Rewini, K. Sadatsharan, N. Sugunaraj, D. F. Selvaraj, S. J. Plathottam, and P. Ranganathan, “Cybersecurity attacks in vehicular sensors,” IEEE Sensors Journal, vol. 20, no. 22, pp. 13752–13767, 2020.
Research Spotlight (Work featured in the reputed IEEE COMST journal, IF: 50.6)
UND feature on our work securing modern distributed energy systems.
3-Minute Thesis Finalist (2021)
Explaining your research in 3 minutes or under.
Invited CARS Talk
A talk on cybersecurity research and applications.
Academically, ask me about securing the electric grid, DERMS, anomaly detection, AI in cybersecurity, doctoral research, interdisciplinary research, or why machine learning models behave differently outside the lab.
Outside my research interests and less academically, I read for leisure (e.g., literature such as narrative non-fiction), game on PC when I can, and strength/weight train. I'm also a culinary enthusiast, enjoy conversations around social/gender psychology, culture, and travel. Travel, culture, languages, or almost anything that begins with, “I've always wondered why people...” are a few conversation directions. You do not need a research question to stop by and say hello.
For those of you who'd like to converse with me in other languages (for fun - I'm not fluent yet), I'm currently learning Italian and Norwegian.