I design AI-driven systems for cybersecurity training, blending reinforcement learning, intelligent tutoring,and adaptive VR to build safer, smarter learning experiences.
Tools & domains I work with: Python, PyTorch, Unity (VR), SwiftUI, RL pipelines, RAG/guardrails, and secure deployment.
The Adaptive Content Engine (ACE) is a reinforcement learning–driven VR training system that personalizes cybersecurity education. It uses PPO and AIRL models to dynamically adjust challenge difficulty based on player performance, improving both engagement and learning efficiency.
SAGE (Student-Focused Adaptive Guidance Engine) is an intelligent tutoring framework that enforces instructor-regulated learning through a three-layer Safety Gatekeeper — role-based, attribute-based, and cognitive access control — built on a knowledge graph of learner state and curricular content.
Cybersecurity work spanning industry and community: auditing access controls and IT governance at RSM US LLP, hands-on labs in malware analysis, password cracking, and exploitation, and founding the University of Missouri's first student-led Cybersecurity Special Interest Group.
M. H. Rayhan, G. R. Edwards, A. Pandey, V. Seth, N. Salvi, N. Glaser, M. Chrysochoou, and P. Calyam, "SAGE: Student-Focused Adaptive Guidance Engine for Intelligent Tutoring with Regulated Learning," in Proc. 2026 IEEE Int. Conf. on Human-Machine Systems (ICHMS), Singapore, Jul. 2026.
