Nur Fajri Al Faridi Hadi
Papers
1
Total Citations
3
H-Index
1
About
Nur Fajri Al Faridi Hadi is a researcher at the intersection of artificial intelligence, biomedical informatics, and smart society technologies. His work focuses on developing machine learning and ensemble learning methods for critical societal challenges, particularly in substance abuse detection and public health. In his highly cited paper "Ensemble Learning Based on Soft Voting for Detecting Methamphetamine in Urine" (2020, 3 citations), Hadi introduced a novel soft voting ensemble approach that combines multiple classifiers to improve the accuracy and reliability of methamphetamine detection from urine samples. This contribution is significant for advancing non-invasive, AI-driven diagnostic tools in forensic toxicology and addiction medicine. Hadi’s research reflects a broader vision of building safe, comfortable, and smart societies coexisting with advanced technology, where AI and robotics serve human well-being. His work has been recognized for its practical implications in combating methamphetamine addiction, a major social problem. As a researcher committed to translating computational innovations into real-world solutions, Hadi continues to explore how ensemble learning and intelligent systems can address pressing health and security challenges in the modern era.
Research Focus
Key Achievements
Top Papers
- 1