Papers
26
Total Citations
629
H-Index
12
About
Wahyu Caesarendra is a prominent researcher whose work spans intelligent manufacturing, condition monitoring, and robotics — fields where he has made substantial contributions bridging machine learning with real-world industrial and assistive applications. He is perhaps best known for his pioneering work in abrasive belt grinding process monitoring, where his application of support vector machines and genetic algorithms to in-process tool condition monitoring has garnered over 200 citations, establishing him as a leading voice in smart manufacturing. His subsequent research introduced deep learning approaches — including convolutional neural networks — to weld seam removal verification and tool wear prediction, demonstrating a consistent drive to advance automation quality through data-driven methods. Beyond manufacturing, Caesarendra has made meaningful inroads into robotics, developing fuzzy-based fault-tolerant control for omnidirectional robots, stereo vision navigation systems, and wearable extra robotic fingers controlled via neural networks. His work in rehabilitation engineering, particularly an EMG-driven upper limb exoskeleton using embedded machine learning, reflects a humanitarian dimension to his research portfolio. With a cumulative citation record exceeding 500 across diverse domains, Caesarendra exemplifies interdisciplinary innovation at the intersection of artificial intelligence, mechanical engineering, and human-centered robotics.
Research Focus
Key Achievements
Top Papers
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- 3Fuzzy-Based Fault-Tolerant Control for Omnidirectional Mobile Robot52 citations · 2020
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