Daniel N'kombo is a cybersecurity researcher and graduate student in the Master of Science in Cybersecurity program at American Public University System (APUS), with a research focus on advanced cyber defense architectures, artificial intelligence, and emerging quantum technologies.
His academic and applied research centers on the development of hybrid quantum–neural artificial intelligence systems for predictive cyber threat detection and adversarial resilience. Daniel's research investigates the potential of combining classical machine learning with quantum-enhanced computation to improve detection accuracy, increase resilience against adversarial manipulation, and support decision-making for executive and organizational leadership.
Daniel's research focuses on essential topics in cybersecurity, including AI-driven intrusion detection, adversarial machine learning, quantum-ready cybersecurity frameworks, risk-informed governance, and safeguarding critical infrastructure. He focuses on transforming complex, emerging technologies into scalable, practical security solutions that address operational, regulatory, and business challenges in real-world contexts.
Daniel's capstone project illustrates a research agenda that combines cybersecurity innovation with strategic risk management and executive decision-making. His long-term academic goal is to conduct advanced doctoral research aimed at enhancing the development of resilient, intelligent, and ethically informed cybersecurity systems for both public and private sectors.