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👋 Hi there! I'm Md Raihan Subhan, a passionate researcher and a dedicated research assistant at Kumoh National Institute of Technology in the Department of IT Convergence Engineering, South Korea.
🔬Currently, I am working as a research assistant in the Pervasive & Intelligent Computing Laboratory under the supervision of Professor Taesoo Jeon. My research topics are anomaly detection in manufacturing execution systems (MES), real-time systems, and blockchain in maritime. My focus lies at the intersection of cutting-edge technologies, where I specialize in Machine Learning, Artificial Intelligence, and anomaly detection. My current research involves the exciting realm of blockchain technology for maritime logistics, exploring innovative solutions to enhance efficiency and security in the maritime industry.
💻 Beyond that, I am deeply engaged in a project related to Manufacturing Execution Systems, leveraging my expertise to streamline processes and drive advancements in manufacturing.
🎓 My educational journey includes a background in science during school, followed by a bachelor's degree in Computer Science and Engineering. I furthered my academic pursuits with a master's in Applied Statistics and Data Science from Bangladesh. Recently, I have pursued my Master's of Engineering from Kumoh National Institute of Technology, diving into the intricacies of IT Convergence Engineering. Presently, I am pursuing Doctor of Philosophy (PhD) in IT Convergence Engineering at Kumoh National Institute of Technology.
🤖 I have a knack for investigating problems from the ground up, analysing issues, and crafting technological solutions. Join me on my journey as I explore the limitless possibilities of technology to make a positive impact.
📫 Let's connect! Feel free to reach out for collaborations, discussions, or just a friendly chat about the fascinating world of technology and research.
In a recent breakthrough, researchers at the Kumoh National Institute of Technology have pioneered an innovative approach to enhancing maritime logistics using blockchain technology.
By integrating blockchain with AI-driven anomaly detection systems, they have developed a method to improve transparency, efficiency, and security in the maritime industry. This cutting-edge technique not only streamlines operations but also ensures robust traceability of goods, thereby reducing the risk of fraud and enhancing trust among stakeholders.
The study's findings hold significant implications for global trade, offering a promising solution to some of the most pressing challenges in maritime logistics. With the potential to transform the industry, this research represents a substantial step forward in leveraging technology for more efficient and secure maritime operations.
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