Peer-reviewed research I've authored or co-authored.
2025
Reza Kermanian, Arash Heydari
A systematic review of 152 studies on large language model deployment in healthcare, introducing the CLDF framework — now cited by other researchers.
2026
Reza Kermanian
Comprehensive review of AI-powered compiler optimization spanning classical heuristics to large language model-based approaches. Published in the Journal of Artificial Intelligence in Electrical Engineering, Issue 57, Spring 2026.
2025
Reza Kermanian, Arash Heydari
Structured review of XAI techniques applied to IDS with comparative analysis of interpretability methods and benchmarking.
2024
Reza Kermanian, Arash Heydari
Optimized deep-learning-based model for intelligent resource management and task scheduling in distributed Fog/Edge environments.
2026
Reza Kermanian
A disciplined case study documenting a complete ML trading research program — 13 pre-registered model variants, anchored walk-forward validation, and permutation-null audits — with transparent reporting of both surviving edges and failed attempts.
Self-authored, not yet released.
Generative Adversarial Networks
An accessible introduction to Generative Adversarial Networks — how two competing neural networks learn to generate realistic data, and why the idea reshaped generative AI.
Self-published — unreleasedReact.js / Frontend Development
A practical guide to React.js for designers and builders creating real web and app interfaces, not just developers.
Self-published — unreleased