Summary
Zabir Al Nazi Nabil is a PhD candidate in Computer Science at UC Riverside with 11 years of industry experience building production-grade ML systems across startups and large platforms. He brings deep expertise in LLMs, information retrieval, computer vision, and medical AI, having shipped cost-conscious, scalable solutions—from an LLM-based search for 3M developer profiles to real-time YOLO ALPR services and state-of-the-art speaker recognition. His background blends research and hands-on engineering: deploying Vertex AI/Arize pipelines, fine-tuning models with RLHF, and optimizing rankers to cut serving costs. As a graduate instructor he teaches data structures and information retrieval while continuing applied research on interpretable, scalable LLM frameworks. Colleagues value his knack for bridging theory and production, and his portfolio shows a consistent focus on explainability and efficient model serving rather than purely experimental prototypes.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Science (B.Sc.), Bachelor of Science (B.Sc.) at Khulna University of Engineering and Technology
Higher Secondary Certificate, Science, Higher Secondary Certificate, Science at RAJUK Uttara Model College
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Riverside
English, Bangla, Spanish, Norwegian