About

I am a doctoral researcher in Computer Science at the University of the Potomac in Washington, DC. My research sits where cybersecurity, machine learning, and applied AI meet: detecting anomalies and insider threats, securing IoT and satellite networks, and understanding how large language models change the way organizations work.

Before research, I spent about a decade building secure software for FinTech and payments — from cryptographic key management and EMV card personalization at Kona Software Lab to identity, event-streaming, and cloud-native banking services at Pubali Bank, and CI/CD and container platforms as a DevOps engineer. That industry work shapes my research: I care about security methods that hold up in production.

Highlights

• 9 peer-reviewed publications (2024–2025) in journals and IEEE conferences, plus an M.Sc. thesis — list
• 223 citations, h-index 6 on Google Scholar (September 2026)
• First author of an IEEE conference paper on insider-threat detection (ICEEI 2025) and a journal article on ML-based anomaly detection
• Peer reviewer for Engineering Applications of Artificial Intelligence (Elsevier) and Discover Computing (Springer Nature)
• CompTIA Security+ and ISC2 Certified in Cybersecurity (CC)

Research interests

• Cybersecurity — anomaly detection, insider-threat detection, IoT and satellite network security
• Machine learning — supervised and unsupervised learning, data analysis, time-series forecasting
• Applied AI — generative AI and large language models
• Quantum computing

Education

• Doctor of Computer Science (in progress) — University of the Potomac, Washington, DC, 2025 – present
• M.S. in Information Technology — Washington University of Science and Technology, 2024 (GPA 4.00, Presidential List)
• M.Sc. in Computer Science and Engineering — BRAC University, 2022
• B.Sc. (Honours) in Computer Science and Engineering — Jahangirnagar University, 2011

Contact

Email norunnabinishan@gmail.com · ORCID · Google Scholar · ResearchGate · LinkedIn · GitHub