Halil Bisgin

Biography

Dr. Bisgin's research spans a wide range of topics from computational social sciences to bioinformatics, where he applies pattern recognition, data analysis, and predictive modeling. At the core of his work are machine learning methods addressing problems in social networks, opinion mining, biomarker discovery, pharmacovigilance, drug repositioning, security analytics, genomics, food contamination, and concussion recovery. He is particularly interested in the cybersecurity aspects of social media analytics — including misinformation, bots, and fake news — and continues to pursue opportunities in bioinformatics, especially next-generation sequencing analysis leveraged for phenotype prediction using machine learning.

Education

• Ph.D., Computer & Information Science — 2012

Current Courses

• CYB 440 — Data Science for Cybersecurity
• DSC 525 — Big Data Analytics
• CYB 540 — Algo ML for Cybersecurity

Selected Publications

• O. Kagnici, T. Judd, H. Bisgin, A. Huseinovic, S. Uludag, A. Aslan, G. LaBelle (2026) “PASS-GAME Lab: A Gamified, Generative AI-Based Cybersecurity Laboratory for Password Security Education” — IEEE Frontiers in Education Conference (FIE)
• O. Kagnici, T. Judd, H. Bisgin, A. Huseinovic, S. Uludag, A. Aslan, G. LaBelle (2026) “GenAI-PassLab: Advancing Password Security Learning Through Generative AI” — ASEE Annual Conference
• A. Aslan, H. Bisgin, S. Uludag (2026) “Session-Robust Dual-Projection Representation Learning for EEG-Based Authentication” — NeurIPS
• O. Kagnici, H. Bisgin, S. Uludag (2025) “Evaluating the Efficacy of GPT-Based Password Generation on Real World Data” — NSF SaTC Conference 2025
• T. Judd, H. Bisgin, A. Huseinovic, M. Derani, S. Uludag (2024) “Coalescing Research into Modular and Safe Educational Cybersecurity Labs with AI Solutions” — IEEE FIE 2024
• M. Knox, C. Tang, H. Bisgin, M. Mani, S. Uludag (2024) “Understanding the Transfer of Knowledge in Introductory Programming Classes” — IEEE FIE 2024
• N. Bisgin, H. Bisgin, D. Hummel, J. Zelner, B. L. Needham (2023) “Did the Public Attribute the Flint Water Crisis to Racism as It Was Happening?” — Journal of Computational Social Science, 6(1), 165–190
• S. Orellana, H. Bisgin (2023) “Using Natural Language Processing to Analyze Political Party Manifestos from New Zealand” — Information, 14(3), 152