About
Salar Farzaneh is an independent researcher and scholar specializing in artificial intelligence security and electrical engineering. He holds an Associate Degree in Electrotechnics from Imam Sadeq Technical and Vocational College, Babol, Iran, and is currently pursuing a Bachelor of Science in Computer Science at University of the People (Pasadena, California, USA).
He has obtained multiple international certifications, including Prompt Engineering Professional Certification, Prompt & AI Engineering Safety Professional Certification (MTF Institute), AI Cybersecurity Solutions: Overview of Applied AI Security, AI Engineer Associate Certificate (School of AI), Elements of AI (University of Helsinki), Machine Learning, DeepSeek AI Masterclass, Internet of Things (IoT), and others.
His research focuses on AI security engineering—including the CIP Layer-3 security model for AI safety against jailbreaking—and psychological dynamics such as psychological dominance and gaslighting (with preprints on PsyArxiv). In parallel, his hardware and electromechanical research spans electrical discharge phenomena, spark and arc physics, high-voltage circuits, electromagnetics, the physical implementation of the H-FMD registered model (featuring local offline AI integration for advanced metal detection and adaptive sensor learning), and innovative mechanical systems like the dual-differential AWD bicycle.
Born: July 18, 1999
Employment
Employment history is unavailable.
Education
Education history is unavailable.
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Publications (3)
- WITHDRAWN: Architectural Engineering and Mathematical Modeling of the Hybrid Fusion Metal Detector (H-FMD) for Deep-Subsurface Extraction and High-Resolution Target Discrimination Save
- H-FMD/HYBRID-X — Reproducible Simulation Code and Results Save
- WITHDRAWN: Architectural Engineering and Mathematical Modeling of the Hybrid Fusion Metal Detector (H-FMD) for Deep-Subsurface Extraction and High-Resolution Target Discrimination Save