Javad Soleiman Meiguni

Missouri University of Science and Technology

Papers

Total Citations

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About

Javad Soleiman Meiguni is a leading researcher in electromagnetic compatibility (EMC) and electrostatic discharge (ESD) phenomena, with a particular focus on automated failure detection and characterization. His most cited work, "Automated Detection and Characterization of ESD-Induced Soft Failures Using Image- and Audio-Based Methods" (2020), introduces innovative techniques that combine audio and image analysis to identify both severe system failures—like complete hangs—and subtle disturbances, such as momentary display glitches. This approach, integrated with a robotic ESD tester, represents a significant advancement in real-time, non-invasive diagnostics for electronic systems. With 4 citations, this paper underscores his contribution to improving reliability testing in consumer electronics and automotive applications. Meiguni’s research bridges the gap between hardware robustness and intelligent monitoring, offering practical solutions for industry. His work is particularly notable for its interdisciplinary nature, merging signal processing, machine learning, and EMC engineering. For students and researchers, Meiguni exemplifies how creative, sensor-driven methodologies can transform traditional ESD testing into a more precise, automated, and scalable process, paving the way for smarter quality assurance in electronics manufacturing.