Papers
9
Total Citations
232
H-Index
6
About
Mukesh Chandra is a multidisciplinary researcher whose work spans digital health technologies and advanced manufacturing, with a particular focus on wire-arc additive manufacturing (WAAM) and artificial intelligence-driven process optimization. His most widely cited contribution, "Digital Technologies, Healthcare and Covid-19: Insights from Developing and Emerging Nations" (2022, 121 citations), demonstrated his ability to address urgent global challenges through a technological lens, examining how digital tools reshaped healthcare delivery across resource-constrained settings during the pandemic. The core of Chandra's research agenda centers on intelligent manufacturing, where he applies machine learning and deep learning to optimize WAAM processes — a high-deposition-rate metal additive manufacturing technique of growing industrial importance. His studies have tackled critical challenges including bead geometry prediction, surface roughness minimization, and real-time anomaly detection using advanced algorithms such as YOLO-based object detection. His work on robotic WAAM systems, particularly involving aluminum alloys, has advanced understanding of mechanical properties, tribological behavior, and deposition quality. With nearly 230 cumulative citations across nine publications, Chandra's research represents a compelling integration of data-driven methodologies with practical manufacturing challenges, making him an emerging voice in smart manufacturing and digital engineering communities.
Research Focus
Key Achievements
Top Papers
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- 7Deep learning for anomaly detection in wire-arc additive manufacturing6 citations · 2023
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