Eko Rudiawan Jamzuri
Papers
5
Total Citations
40
H-Index
3
About
Eko Rudiawan Jamzuri is a robotics and artificial intelligence researcher whose work centers on computer vision, deep learning, and humanoid robot systems. He is best known for his contributions to real-time object detection in robotic applications, particularly through his development and adaptation of YOLO-based detection frameworks for humanoid soccer robots. His most influential work, "The Deep Learning Development for Real-Time Ball and Goal Detection of Barelang-FC" (2017), has garnered 31 citations and demonstrated how deep learning architectures could be practically integrated into competitive humanoid robotics, advancing the field of robot perception significantly. Jamzuri's research is closely tied to the BarelangFC robot platform, a humanoid system developed for the Kontes Robot Indonesia (KRI) competition. His contributions span object detection and distance measurement coordination systems, CPU-efficient neural network algorithms for marathon robots, and most recently, speech-based question answering interfaces for humanoid robots. This progression reflects a broadening research vision — from visual perception toward full human-robot interaction. His 2024 work on natural language processing integration signals an exciting evolution in his focus. For students interested in applied AI and competitive robotics, Jamzuri's body of work offers a practical, technically rigorous roadmap for building intelligent, autonomous humanoid systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Humanoid robot magic show performance3 citations · 2023
- 3
- 4
- 5