Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Published on by Neuroscientists

Mr. Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Mr.  Koagne Longpa Tamo Silas, University of Dschang, Cameroon.

Koagne Longpa Tamo Silas is a dedicated researcher in the field of medical physics, specializing in automation, artificial intelligence, and electronic system design. His academic journey from Bamenda State University to Dschang State University reflects his continuous pursuit of knowledge and innovation. His contributions to circuit simulation, embedded systems, and artificial neural networks have established him as a promising figure in medical physics.

Profile

Google Scholar

🎓 Early Academic Pursuits

Born on July 12, 1998, in Mbouda, Cameroon, Koagne Longpa Tamo Silas displayed a keen interest in science and technology from a young age. His passion for physics and engineering led him to pursue higher education at Bamenda State University, where he embarked on an academic journey in Electrical and Power Engineering. His undergraduate studies, from November 2015 to August 2018, laid the foundation for his expertise in electrical systems, automation, and circuit design. Eager to expand his knowledge, he continued his postgraduate studies in the same field at Bamenda State University from September 2018 to July 2020, honing his skills in power engineering and applied electronics.

🚀 Professional Endeavors

Determined to deepen his expertise, Koagne Longpa Tamo Silas transitioned into the field of physics, enrolling as a Ph.D. student at Dschang State University in December 2022. His academic pursuits in the Department of Physics align with his interests in medical physics, where he integrates automation, applied computer science, and electronics to innovate in the field. As a dedicated researcher, he continues to engage with the Faculty of Science at Dschang State University, contributing to the academic and scientific community with his research in medical physics and embedded systems.

🤖 Contributions and Research Focus

Koagne Longpa Tamo Silas has dedicated his research efforts to the intersection of medical physics, automation, and artificial intelligence. His work encompasses Analog Artificial Neural Networks, Embedded Systems, Circuit Simulation, Digital and Analog Electronics, and Microcontroller Programming. His proficiency in tools like Spice Simulation, Cadence Virtuoso, and Electronic Design Automation allows him to design and optimize medical devices and automated systems. His research aims to enhance diagnostic and therapeutic tools in medical physics by leveraging artificial intelligence and embedded systems.

🏆 Accolades and Recognition

Throughout his academic and research career, Koagne Longpa Tamo Silas has garnered recognition for his contributions to medical physics and electronics. His innovative approach to circuit simulation and signal processing has positioned him as a promising researcher in his field. His dedication to advancing medical technologies has earned him the respect of his peers and mentors, as he continues to contribute valuable insights to the scientific community.

🌐 Impact and Influence

Through his academic journey and research, Koagne Longpa Tamo Silas has influenced the way automation and artificial intelligence are integrated into medical physics. His work in digital electronics and microcontroller programming is paving the way for innovative solutions in the medical field. His contributions extend beyond research, as he actively engages with students and researchers, fostering a culture of knowledge-sharing and scientific exploration.

 

Publication

  • A High-Resolution Non-Volatile Floating Gate Transistor Memory Cell for On-Chip Learning in Analog Artificial Neural Networks
    Authors: KLT Silas, DTA Bernard, FT Bernard, L Jean-Pierre, GW Ejuh
    Year: 2025

 

  • Breast Cancer Diagnosis with Machine Learning Using Feed-Forward Multilayer Perceptron Analog Artificial Neural Network
    Authors: B Djimeli-Tsajio Alain, KLT Silas, LT Jean-Pierre, N Thierry, GW Ejuh
    Year: 2024

 

  • Design and Implementation of a Digital Breath Alcohol Detection System with SMS Alert and Vehicle Tracking on Google Map
    Author: KLT Silas
    Year: 2020

 

  • Design and Realization of an Electronic Attendance System Based on RFID with an Automatic Door Unit
    Author: MK Jules
    Year: 2018

 

🎯 Conclusion

With a vision to transform medical physics through automation and AI-driven technologies, Koagne Longpa Tamo Silas is on a path to making significant contributions to healthcare innovation. His passion, dedication, and expertise ensure that his research will continue to shape the future of medical technology, leaving a lasting impact on both academia and practical applications in the field.

 

Xiaobing Yan | Neurotechnology | Best Researcher Award

Published on by Neuroscientists

Prof. Xiaobing Yan | Neurotechnology | Best Researcher Award

Prof. Xiaobing Yan, Hebei University, China.

Professor Xiaobing Yan is a distinguished researcher specializing in novel memory devices and memristor-based brain-inspired chip technologies. As a Senior Member of IEEE and a reviewer for leading journals, he has made significant contributions to the field of neuromorphic engineering. His outstanding achievements include recognition as a Young Changjiang Scholar and a Young Top-notch Talent under China’s National Ten Thousand Talents Program. With over 120 high-impact publications, 5,600+ citations, and an H-index of 40, he is globally recognized among the top 2% of scientists. His research has been supported by several prestigious national and provincial funding programs.

Profile

Scopus

🎓 Early Academic Pursuits

Xiaobing Yan embarked on his academic journey with a deep passion for electronics and information engineering. His early years were marked by an unwavering dedication to understanding the complexities of memory devices and neuromorphic systems. As he progressed through his studies, his curiosity and drive led him to explore the intersection of artificial intelligence and hardware development. His rigorous academic training laid a solid foundation for his future contributions to next-generation computing technologies.

💪 Professional Endeavors

Currently serving as a Professor at the Institute of Life Science and Green Development, Hebei University, Xiaobing Yan has established himself as a distinguished leader in the field of electronic engineering. He is a Doctoral Supervisor and a Senior Member of IEEE, a testament to his vast expertise and influence in the scientific community. His role extends beyond academia, as he actively engages in national-level research programs and collaborates with top-tier research institutions. His professional journey is a testament to his commitment to pioneering advancements in neuromorphic computing and memristor-based brain-inspired chip technologies.

🤖 Contributions and Research Focus

Xiaobing Yan’s research primarily revolves around novel memory devices and brain-like computing systems. His work has been instrumental in the advancement of memristor-based chip technologies, which hold the potential to revolutionize artificial intelligence hardware. By bridging the gap between neuroscience and semiconductor innovation, he is contributing to the development of energy-efficient, high-performance computing architectures. His research projects, funded by prestigious national programs, aim to push the boundaries of nanoelectronics and intelligent systems.

🏆 Accolades and Recognition

Xiaobing Yan’s groundbreaking work has earned him widespread recognition. In 2019, he was honored as a Young Changjiang Scholar by the Ministry of Education and selected as a Young Top-notch Talent under the National Ten Thousand Talents Program. In 2024, he further cemented his legacy by winning the Excellence Award at the National Disruptive Innovation Technology Competition. His contributions are not only recognized in China but also on a global scale, as he has been listed among the top 2% of scientists worldwide by Stanford University.

🌟 Impact and Influence

With over 120 high-impact publications and more than 5,600 citations, Xiaobing Yan’s research has significantly shaped the field of electronics and artificial intelligence. His H-index of 40 reflects the depth and relevance of his contributions. As a reviewer for prestigious journals such as Nature Electronics, Advanced Materials, and ACS Nano, he plays a crucial role in shaping the direction of cutting-edge research. His influence extends beyond his publications, as he mentors young researchers and fosters collaborations that drive innovation in neuromorphic computing.

🚀 Legacy and Future Contributions

As a leader in disruptive technology and nanoelectronics, Xiaobing Yan is poised to continue pushing the boundaries of scientific discovery. His ongoing research projects, including multiple National Key R&D initiatives and collaborations with leading institutions, demonstrate his commitment to pioneering breakthroughs in brain-inspired computing. With his vision and expertise, he is set to leave a lasting legacy in the development of next-generation intelligent systems, shaping the future of artificial intelligence and semiconductor technology.

Publication

  1. In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

    • Authors: H. Lin, Haipeng; J. Ou, Jiali; Z. Fan, Zhen; X. Gao, Xingsen; J. Liu, Junming
    • Year: 2025

 

  1. Ultra robust negative differential resistance memristor for hardware neuron circuit implementation

    • Authors: Y. Pei, Yifei; B. Yang, Biao; X. Zhang, Xumeng; S. Li, Shushen; X. Yan, Xiaobing
    • Year: 2025

 

  1. Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models

    • Authors: W. Yue, Wenshuo; K. Wu, Kai; Z. Li, Zhiyuan; R. Huang, Ru; Y. Yang, Yuchao
    • Year: 2025

 

  1. Memristor-based feature learning for pattern classification

    • Authors: T. Shi, Tuo; L. Gao, Lili; Y. Tian, Yang; X. Yan, Xiaobing; Q. Liu, Qi
    • Year: 2025

 

  1. Harnessing spatiotemporal transformation in magnetic domains for nonvolatile physical reservoir computing

    • Authors: J. Zhou, Jing; J. Xu, Jikang; L. Huang, Lisen; X. Yan, Xiaobing; S.T. Lim, Sze Ter
    • Year: 2025

 

  1. Flexoelectric Effect in Thin Films: Theory and Applications

    • Authors: X. Jia, Xiaotong; R. Guo, Rui; J. Chen, Jingsheng; X. Yan, Xiaobing
    • Year: 2025

 

  1. Deoxyribonucleic acid brick crystals-based memristor as an artificial synapse for neuromorphic computing

    • Authors: Z. Wang, Zhongrong; X. Liu, Xinran; J. Li, Jiahang; J. Lou, Jianzhong; X. Yan, Xiaobing
    • Year: 2025

 

  1. Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors

    • Authors: Z. Guo, Zhenqiang; G. Duan, Guojun; Y. Zhang, Yinxing; Y. Faraj, Yousef; X. Yan, Xiaobing
    • Year: 2025

 

  1. Achieving over 10 % efficiency in kesterite solar cells via selenium-free annealing

    • Authors: Q. Zhou, Qing; Y. Cong, Yijia; H. Li, Hao; Y. Sun, Yali; W. Yu, Wei
    • Year: 2024

 

  1. Hardware implementation of memristor-based artificial neural networks

  • Authors: F.L. Aguirre, Fernando L.; A. Sebastian, Abu; M. Le Gallo, Manuel; S. Matias Pazos, Sebastian; M. Lanza, Mario
  • Year: 2024

 

Conclusion

Professor Yan’s work plays a pivotal role in advancing memory technology and brain-inspired computing. His extensive research contributions and leadership in high-impact projects underscore his expertise in developing next-generation computing technologies. His global recognition and numerous accolades highlight his influence in the field, positioning him as a key figure in neuromorphic engineering and memory device innovation.