Research

Research Overview

My research lies at the intersection of cybersecurity, artificial intelligence, and data analytics, with a focus on enhancing decision-making, advancing AI explainability and reliability, and improving human-AI collaboration. My work is problem-centered and interdisciplinary, drawing on AI model development, design science, computational experiments, and empirical studies to address real-world challenges in cybersecurity, education, healthcare, and business analytics.

Google Scholar Profile | ORCID

Research Keyword Cloud

Main Research Areas

Human-AI Collaboration in Cyber Defense

Context-Aware AI Explainability for Cyber Defense Analysis

This research investigates how cybersecurity analysts interact with AI systems during incident detection, triage, and response. It focuses on identifying analysts' context-aware explainability needs and designing AI systems that are adaptive, transparent, and aligned with human cognitive processes.

AI-Powered Threat Detection

This research stream includes work on insider threat detection, transformer-based behavioral modeling, mobile fleeceware detection, dark patterns in deceptive apps, smishing detection, BERT-based and LLM-based phishing analysis, and explainable and interpretable threat detection.

Social Media Analytics for Cybersecurity and Business Insights

This research applies NLP and text analytics to Reddit discourse, cybersecurity competition communities, informal learning in cybersecurity, ESG discourse analysis, public sentiment, and broader digital discourse.