My research centers on language models and AI alignment. I am particularly interested in how model design and training choices shape capabilities and behavior, and in developing models that are more capable, reliable, and aligned.
I hold a B.S. in Computer Science, with minors in Mathematics and Physics, from the University of North Carolina at Pembroke, where I worked with Dr. Prashanth BusiReddyGari and Dr. Shaohu Zhang. I was an AI Safety Research Fellow at Algoverse. I completed the AI Safety Fundamentals Fellowship (AISF) with MIT AI Alignment (MAIA) and BlueDot Impact's Technical AI Safety course.
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DPBench: Structural Determinants of Multi-Agent LLM Coordination Under Simultaneous Resource Contention
Najmul Hasan and Prashanth BusiReddyGari. Preprint, 2026. Code
Benchmarking Large Language Models for Zero-shot and Few-shot Phishing URL Detection
Najmul Hasan and Prashanth BusiReddyGari. LAW Workshop, NeurIPS 2025.
Honeypot Protocol
Najmul Hasan. AI Control Hackathon, Apart Research, 2026. Code
SAGE
A Python framework in which language-model agents research, discuss, and synthesize answers through a structured workflow.
Sift
An autonomous IT ticket triage system that produces diagnoses, resolution steps, and escalation decisions.


