Postdoctoral at ICT Convergence Research Center, South Korea
Dr. Syamsul Rizal is an Assistant Professor at Telkom University, Indonesia, and a postdoctoral researcher at Kumoh National Institute of Technology, South Korea, with expertise in machine learning, AI, and blockchain integration. With over five years of teaching experience, he instructs courses in programming and AI, fostering the next generation of tech innovators. His research spans real-time locating systems, biomedical applications of AI, and recently, blockchain with AI, showcasing his focus on emerging, interdisciplinary technology. Dr. Rizal has a strong publication record with contributions to prominent conferences and journals, demonstrating his commitment to advancing AI and machine learning. Honored with a Best Thesis Award and scholarships, he combines technical skill, academic rigor, and practical application in his work. Known for his collaborative spirit and leadership in international research settings, Dr. Rizal is recognized for his contributions to applied AI and his role in innovative technology development.
Professional profile
Educationđź“š
Dr. Syamsul Rizal completed his Master’s and Ph.D. programs in the Department of IT Convergence at the Kumoh National Institute of Technology, South Korea, from 2013 to 2018. His advanced studies focused on integrating emerging technologies across fields such as networked systems, IoT, and AI. As a team leader in the Networked Systems Laboratory, he worked on projects related to ISA100.11a, data virtualization, and image and video processing, gaining hands-on experience in cutting-edge technology. During his doctoral studies, he was honored with a Best Thesis Award in 2015, highlighting his research excellence and innovative approach. His education, supported by a scholarship at Kumoh National Institute of Technology, provided a robust foundation in both theoretical and applied aspects of information technology. Dr. Rizal’s academic journey has equipped him with interdisciplinary expertise, enabling him to address complex challenges in machine learning, blockchain, and AI-driven solutions in his professional career.
Professional Experience🏛️
Dr. Syamsul Rizal has a diverse professional background that spans academic and applied research roles. Currently, he is an Assistant Professor at Telkom University, Indonesia, where he has been teaching since 2019, specializing in programming, artificial intelligence, and mobile application development. His teaching focuses on empowering students with foundational and advanced skills in Python, Java, and C. Alongside teaching, Dr. Rizal is actively involved in research, particularly in machine learning, with projects like AI-driven tea leaf classification. Since 2023, he has also served as a postdoctoral researcher at Kumoh National Institute of Technology in South Korea, where he is developing blockchain systems integrated with AI, reflecting his commitment to emerging technologies. Dr. Rizal’s previous experience includes a postdoctoral role at DGIST, South Korea, where he worked on real-time locating systems and deep learning algorithms for automotive applications. His experience highlights a strong interdisciplinary approach and dedication to innovation.
🔬 Research Interest
Dr. Syamsul Rizal’s research interests are rooted in interdisciplinary applications of advanced technology, particularly in machine learning, AI integration, and networked systems. His work spans diverse areas such as data reconstruction, real-time locating systems (RTLS), and biomedical engineering applications. Dr. Rizal’s research also emphasizes the application of machine learning algorithms for classification tasks, including innovative projects like tea leaf classification and brain stroke detection. He has explored machine learning in biomedical contexts, using techniques like convolutional neural networks (CNNs) for medical image analysis, including retinal pathology and colon cancer classification. Further extending his expertise, Dr. Rizal is engaged in developing blockchain technology with AI capabilities, underscoring his focus on pioneering solutions that leverage AI for security and scalability in decentralized networks. His research reflects a commitment to advancing the practical impact of machine learning and AI across fields as diverse as agriculture, healthcare, and blockchain technology.
🏆Awards and Honors
Dr. Syamsul Rizal has been recognized for his academic excellence and contributions to the field of technology through several awards and honors. Notably, he received the Best Thesis Award in 2015 from the Kumoh National Institute of Technology, South Korea, where he completed both his Master’s and Doctoral studies. This award highlights his exceptional research skills and his innovative contributions during his graduate studies, specifically in networked systems and real-time data communication. Additionally, he was granted a prestigious scholarship to join the Networked System Laboratory at Kumoh, supporting his research in cutting-edge areas such as IoT, virtualization, and image and video processing. These accolades underscore Dr. Rizal’s dedication to advancing technological innovation and his role as a leader in applied research, contributing valuable insights and advancements in fields ranging from machine learning and artificial intelligence to networked systems and data science.
Conclusion
Dr. Syamsul Rizal is a compelling candidate for the Best Researcher Award due to his robust background in machine learning, AI, and systems engineering, combined with a strong publication record and international experience. By further expanding his publication reach and collaborative initiatives, Dr. Rizal could enhance his profile and make an even stronger case for this award, which recognizes impactful and innovative research.
Publications top notedđź“ś
- ND Miranda, L Novamizanti, S Rizal
Title: “Convolutional Neural Network pada klasifikasi sidik jari menggunakan RESNET-50”
Journal: Jurnal Teknik Informatika
Year: 2020
Citations: 88
- YN Fu’adah, I Wijayanto, NKC Pratiwi, FF Taliningsih, S Rizal, …
Title: “Automated classification of Alzheimer’s disease based on MRI image processing using convolutional neural network (CNN) with AlexNet architecture”
Journal: Journal of Physics: Conference Series
Year: 2021
Citations: 57
- S Rizal, N Ibrahim, NORKC PRATIWI, S Saidah, RYNUR FUĂ‚
Title: “Deep Learning untuk Klasifikasi Diabetic Retinopathy menggunakan Model EfficientNet”
Journal: ELKOMIKA
Year: 2020
Citations: 18
- S Rizal, T Kartika, GA Septia
Title: “Studi Etnobotani Tumbuhan Obat di Desa Pagar Ruyung Kecamatan Kota Agung Kabupaten Lahat Sumatera Selatan”
Journal: Sainmatika
Year: 2021
Citations: 17
- NORKC PRATIWI, NUR IBRAHIM, YNUR FUĂ‚, S RIZAL
Title: “Deteksi Parasit Plasmodium pada Citra Mikroskopis Hapusan Darah dengan Metode Deep Learning”
Journal: ELKOMIKA
Year: 2021
Citations: 15
- AA Pramudita, Y Wahyu, S Rizal, MD Prasetio, AN Jati, R Wulansari, …
Title: “Soil water content estimation with the presence of vegetation using ultra wideband radar-drone”
Journal: IEEE Access
Year: 2022
Citations: 13
- AA Santosa, RYN Fu’adah, S Rizal
Title: “Deteksi Penyakit pada Tanaman Padi Menggunakan Pengolahan Citra Digital dengan Metode Convolutional Neural Network”
Journal: Journal of Electrical and System Control Engineering
Year: 2023
Citations: 10
- ME Abdulfattah, L Novamizanti, S Rizal
Title: “Super Resolution pada Citra Udara menggunakan Convolutional Neural Network”
Journal: ELKOMIKA
Year: 2021
Citations: 10
- I Wijayanto, S Rizal, S Hadiyoso
Title: “Epileptic electroencephalogram signal classification using wavelet energy and random forest”
Journal: AIP Conference Proceedings
Year: 2023
Citations: 9
- S Saidah, YN Fuadah, F Alia, N Ibrahim, R Magdalena, S Rizal
Title: “Facial skin type classification based on microscopic images using convolutional neural network (CNN)”
Conference: 1st International Conference on Electronics, Biomedical …
Year: 2021
Citations: 9
- YN Fu’adah, S Sa’idah, I Wijayanto, N Ibrahim, S Rizal, R Magdalena
Title: “Computer Aided Diagnosis for Early Detection of Glaucoma Using Convolutional Neural Network (CNN)”
Conference: 1st International Conference on Electronics, Biomedical …
Year: 2021
Citations: 9
- HM Lathifah, L Novamizanti, S Rizal
Title: “Fast and accurate fish classification from underwater video using you only look once”
Journal: IOP Conference Series: Materials Science and Engineering
Year: 2020
Citations: 8
