Radityo Fajar Pamungkas is a dedicated researcher with a Master’s degree in Electronics Engineering from Kookmin University, South Korea, and a Bachelor’s in Electrical Engineering from the University of Indonesia. His expertise spans streaming time series forecasting, adaptive anomaly detection, and edge-cloud computing integration, applied to smart factories and solar farms. At WiComAl Laboratory, Kookmin University, he conducted significant research and published three international papers, while also managing multiple projects and developing industrial standards. His notable projects include designing 5G IoT platforms and enhancing Virtual Power Plants with AI-driven solutions. Certified in deep learning, AI fundamentals, and green digital skills, Radityo combines strong analytical and technical skills with effective communication and project management abilities.
Professional Profile:
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🎓Education:
Radityo Fajar Pamungkas earned his Master of Science in Electronics Engineering from Kookmin University in Seoul, South Korea, graduating in February 2024 with an outstanding GPA of 4.44/4.50. His thesis, titled “A Hybrid Approach of ConvLSTM-DT and GPT-4 for Real-time Anomaly Detection Decision Support in Edge-Cloud Environments,” reflects his deep expertise in anomaly detection and edge-cloud integration. He was also recognized as an Excellent Researcher Awardee. Prior to this, he completed his Bachelor of Engineering in Electrical Engineering at the University of Indonesia, where he focused on Energy and Power System Engineering and graduated in August 2021 with a GPA of 3.48/4.00. His undergraduate thesis was “Hot Spot Detection Application for Solar PV Module Based on Digital Image Processing.”
🏢Work Experience:
As a Research Assistant at WiComAl Laboratory, Kookmin University, from February 2022 to February 2024, Radityo Fajar Pamungkas specialized in streaming time series forecasting models and adaptive anomaly detection algorithms. During his tenure, he published three international papers and secured four domestic patents. He was instrumental in developing an industrial standard edge server tailored for smart factory applications and successfully managed multiple research projects simultaneously.
🏆Certifications:
Radityo Fajar Pamungkas has enhanced his expertise through various certifications: he completed the Deep Learning Networks Specialization from Coursera, offered by DeepLearning.ai, and earned the Microsoft Azure AI Fundamentals certification. Additionally, he obtained the Green Digital Skills certification from Inco Academy and pursued learning in machine learning development through Dicoding. These certifications complement his academic and research background, further strengthening his skills in AI and machine learning
Publication Top Notes:
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A hybrid approach of ConvLSTMBNN-DT and GPT-4 for real-time anomaly detection decision support in edge-cloud environments
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Fast Partial Shading Detection on PV Modules for Precise Power Loss Ratio Estimation Using Digital Image Processing
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Design and Implementation of a 2D MIMO OCC System Based on Deep Learning
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Intelligent IoT Platform for Multiple PV Plant Monitoring
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A Novel Approach for Efficient Solar Panel Fault Classification Using Coupled UDenseNet