KOAGNE LONGPA TAMO Silas is a dedicated Cameroonian PhD student in Physics, specializing in Medical Physics at Dschang State University, Cameroon. Born on July 12, 1998, in Mbouda, he is committed to advancing knowledge in automation and applied computer science. His research focuses on Artificial Neural Networks (ANNs) and Embedded Systems, with a keen interest in Analog Electronics and Medical Physics applications. Silas’ academic journey spans over multiple disciplines, including Physics, Electronics, and Embedded Systems, and he holds both a Master’s and Bachelor’s degree in Physics. He is also a teacher and has professional experience in the electronics field, showcasing a diverse skill set in education, programming, and practical applications.
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Education 📖🎓
Silas holds a Master’s degree in Physics (Specialization: Electronics) from Dschang State University (2022) and a Bachelor’s degree in Physics from the same institution (2021). He also earned a DIPET 2 in Electronics (2020) from the University of Bamenda, where he focused on Embedded Systems. His academic achievements include significant research in Artificial Neural Networks, with a thesis titled “Specification and implementation of multilayer perceptron analog artificial neural networks.” Silas’ strong foundation in medical physics and electronics stems from both his undergraduate and postgraduate studies. In addition, he has successfully completed industrial internships related to electronics and high-voltage systems, gaining hands-on expertise in maintenance and system implementation.
Experience 💼🔧
Silas has gathered substantial professional experience across multiple industries and educational roles. His industrial internships include work with HYTECHS-Yaoundé and MEECH CAM Sarl-Yaoundé, where he focused on maintaining and installing printing systems and electrical networks. In his teaching career, Silas serves as an Electronics teacher at Government Technical College Ngombo-ku and previously as a Computer Science junior lecturer at Higher Technical Teacher Training College Bambili. His hands-on experience in embedded systems and electronics teaching has shaped his approach to learning, blending theoretical knowledge with real-world applications. Silas has also supervised and collaborated on student research projects, contributing significantly to their academic growth.
Research Focus 🔬💡
Silas’ research is focused on Medical Physics, particularly within the domains of automation, Artificial Neural Networks (ANNs), and embedded systems. He aims to develop and optimize analog artificial neural networks for medical applications, exploring their use in areas such as signal processing, system automation, and diagnostics. His work extends to circuit simulation, microcontroller programming, and electronics design, with applications in the fields of digital electronics and communication systems. Silas is interested in the intersection of physics, medicine, and automation, leveraging technology to enhance healthcare systems. Through his PhD, he aims to make substantial contributions to the integration of machine learning with medical devices, improving diagnostics and treatment accuracy.
Publication Top Notes 📑📚
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“Specification and Implementation of Multilayer Perceptron Analog Artificial Neural Networks”
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“Design and Implementation of a Digital Breath Alcohol Detection System with SMS Alert”
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“Design and Realization of an Electronic Attendance System Based on RFID with Automatic Door Unit”