I specialize in object detection, image processing, and deep learning, with a core focus on agricultural, medical, and industrial automation. I build and deploy robust, real-world AI detection systems using PyTorch and TensorFlow, specifically optimizing models for high-accuracy visual recognition, medical, and plant disease identification. I also like to tinker my software and hardware, creating tools for my productivity. My hobby is playing video games and sometimes I'd like to develop a game myself.
- Deep Learning & Computer Vision: Designing and fine-tuning state-of-the-art object detection workflows, particularly focusing on lightweight YOLO architectures for edge deployment.
- Agricultural and Industrial Automation: Engineering systems for automated crop counting, disease classification, and precision yield estimation. Implementing AI-driven quality control and defect detection systems in manufacturing processes.
- Medical Imaging Advancement: Developing AI models for early disease detection and medical image analysis, enhancing diagnostic accuracy and efficiency.
- Mentorship & Community: Certified TensorFlow Developer and former Machine Learning Mentor at
Bangkit Academy 2024 by Google, GoTo and Traveloka, where I guided over 25 students through model training, optimization, and production deployment. - Professors' Assistant: Served as a technical/laboratory lecturer at Mulawarman University, supporting undergraduate courses in AI, Machine Learning, Data Structures & Algorithms, and Object-Oriented Programming.
I hold a Bachelor of Computer Science (B.CS. / S.Kom.) from Universitas Mulawarman. Beyond engineering, I actively contribute to academic research in applied AI. I have co-authored multiple Scopus-indexed papers, including Q1 journal submissions in Smart Agricultural Technology and Artificial Intelligence in Agriculture.
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