Dipanjan Ghosh

Hitachi Global Storage Technologies (United States)

Papers

Total Citations

H-Index

About

Dipanjan Ghosh is a researcher at the intersection of artificial intelligence and industrial maintenance, with a primary focus on automated visual inspection and predictive quality control. His most cited work, "Guided Visual Inspection enabled by AI-based Detection Models" (2021), addresses a critical industry challenge: preventing equipment breakdowns and downtime through proactive, AI-driven maintenance. Ghosh’s contributions center on developing deep learning models that automate the detection of defects and anomalies in visual data, streamlining safety, quality control, and asset management processes. While his citation count is still growing—reflecting the emerging nature of his research area—his work is foundational for industries seeking to transition from reactive to predictive maintenance. By integrating computer vision with guided inspection workflows, Ghosh is helping to reduce human error and operational costs. His research holds particular promise for manufacturing, energy, and infrastructure sectors, where automated visual inspection is becoming a key enabler of Industry 4.0. As the demand for intelligent, real-time monitoring systems rises, Ghosh’s contributions are poised to have lasting impact on how industrial assets are maintained and managed.