Mr. Vikas Kumar Sinha | Electronics and Communication ENgineering | Young Scientist Award

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Mr. Vikas Kumar Sinha | Electronics and Communication ENgineering | Young Scientist Award  

Mr. Vikas Kumar Sinha ,NIT Rourkela, India 🎓

Professional Profile

🎓📚 Early Academic Pursuits

Born on July 8, 1991, Vikas Kumar Sinha demonstrated an early affinity for academics. His foundational education was marked by excellence, securing 86.17% in his Class 10th from the Chhattisgarh Board of Secondary Education in 2006. This was followed by an impressive 83.67% in Class 12th in 2008. Vikas pursued his Bachelor of Engineering in Electronics & Telecommunication at Government Engineering College, Bilaspur, where he graduated with a CGPA of 7.35 in 2012. He further honed his technical skills by completing a Master of Technology in Control Systems from Manipal Institute of Technology, Karnataka, in 2015, with a CGPA of 7.47. His academic journey culminated in a Ph.D. in Electronics & Communication from the National Institute of Technology Rourkela, India, in 2024, achieving a CGPA of 8.60.

💼 Professional Endeavors

Vikas embarked on his professional career as an Assistant Professor at J.K. Institute of Engineering, Bilaspur, Chhattisgarh, from February 2017 to July 2018. His industry experience includes a significant tenure as an M.Tech Trainee at CSIR – Central Scientific Instruments Organisation, Chandigarh, from July 2014 to May 2015. During his academic and professional career, he has acquired expertise in various technical skills, including MATLAB, Linux, Python, Arduino IDE, STM Cube IDE, Embedded C, Digital Signal Processing, and Machine Learning.

🔬 Contributions and Research Focus

Vikas’s research contributions are substantial, focusing on real-time ECG signal processing, R-peak detection, and arrhythmia classification. His Ph.D. work involved significant projects using both 8-bit and 32-bit microcontrollers, MATLAB, Python, and Raspberry Pi. His innovative projects include the development of an IoT camera integrated with temperature and accelerometer sensors for image capturing during sudden movements.

🏆 Accolades and Recognition

Vikas’s academic excellence and research prowess have been recognized through various accolades. His noteworthy publication includes a book chapter titled “Customized Deep Learning Algorithm for Drowsiness Detection using Single Channel EEG Signal,” co-authored with notable researchers and published in “Artificial Intelligence-Based Brain-Computer Interface” by Academic Press in 2022.

🌐 Impact and Influence

Vikas has made a significant impact in the field of Electronics and Communication through his research and publications. His work on real-time ECG signal processing and arrhythmia classification has the potential to contribute to advancements in medical diagnostics and patient monitoring systems. His technical projects demonstrate a blend of innovation and practical application, positioning him as a forward-thinking researcher and educator.

🌟 Legacy and Future Contributions

With a strong foundation in both theoretical knowledge and practical application, Vikas Kumar Sinha is poised to continue making significant contributions to the field of Electronics and Communication. His future endeavors are expected to focus on leveraging his expertise to develop advanced diagnostic tools and contribute to the growth of the academic and research community.

📖Publications Top Noted: 

Vinny Junior Foba Kakeu | Electrical engineering | Best Researcher Award

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Vinny Junior Foba Kakeu | Electrical engineering | Best Researcher Award

University Of Douala, Cameroon

Author Profile

Early Academic Pursuits

Vinny Junior Foba Kakeu demonstrated exceptional academic performance from an early age. He completed his Baccalaureate in electrical engineering with honors in 2014/2015, being recognized as the regional major. This academic excellence continued throughout his studies at ENSET Douala and IUT Douala, where he consistently achieved top ranks and honors. Notably, he obtained the DIPET 1 and DIPET 2 in electrical engineering with honors, securing the best end-of-study project and dissertation awards. His relentless pursuit of knowledge culminated in a Master 2 Research degree from the University of Douala in 2021/2022, where he was the valedictorian and best end-of-study dissertation awardee.

Professional Endeavors

Vinny's professional journey began with academic internships at LMP Construction and SETCAM in 2016 and 2017, respectively. These internships provided practical experience in the field of electrical engineering. Since 2021, he has been imparting his knowledge as a part-time teacher at various prestigious institutions, including ENSET University of Douala, IUT University of Douala, ISETAG, IUGET, and the NDI-SAMBA Polytechnic Institute. His teaching repertoire includes a wide range of subjects, from network simulation and energy quality to electromagnetic compatibility and intelligent networks. In addition, since December 2021, he has been assigned to MBANGA Technical High School, contributing significantly to the educational development in the region.

Contributions and Research Focus

His contributions to the field of electrical engineering and artificial intelligence are substantial. His research focuses on optimizing energy efficiency, supervised deep learning applications for engineering problems, and the analysis of smart grids using deep learning tools. He has been a scientific researcher in the field of deep learning and artificial intelligence algorithms, publishing numerous scientific articles and books. His notable research works include projects on the design and production of an autonomous mobile robot controlled by Bluetooth and optimizing the reliability of smart grids using the PSO algorithm.

Accolades and Recognition

Throughout his academic and professional career, His received numerous accolades. He was the top student in his classes multiple times and was honored with the best end-of-study project and dissertation awards during his DIPET 1, DIPET 2, and Master 2 Research studies. His dedication to excellence has been consistently recognized, highlighting his profound impact on his peers and the academic community.

Impact and Influence

His impact extends beyond teaching and research. He has been a reviewer for many scientific journals, contributing to the advancement of knowledge in his field. His scientific publications have been widely recognized and cited, influencing ongoing research in smart grids, deep learning, and energy optimization. His collaborative works with other researchers have resulted in significant advancements, such as fault detection, classification, and location in power distribution smart grids using smart meters data.

Legacy and Future Contributions

His legacy is marked by his contributions to academia, research, and practical applications in electrical engineering and artificial intelligence. His work on smart grids and deep learning has set a foundation for future innovations in these fields. As an author and educator, he continues to inspire and mentor the next generation of engineers and researchers. His future contributions are anticipated to further advance the optimization of energy efficiency and the application of deep learning in engineering, solidifying his role as a pioneer in his field.

Notable Publications 

A review of Cameroonian medicinal plants with potentials for the management of the COVID-19 pandemic

Optimal reliability of a smart grid

Fault detection, classification and location in power distribution smart grid using smart meters data

Fault diagnosis of an induction motor based on fuzzy logic, artificial neural network and hybrid system

Sliding mode control of a three-phase parallel active filter based on a two-level voltage converter

A hybrid model for forecasting the consumption of electrical energy in a smart grid

Implementation of quadratic dynamic matrix control on arduino due ARM cortex-M3 microcontroller board

Optimal reconfiguration of power distribution systems based on symbiotic organism search algorithm

Forecasting of electrical energy consumption of households in a smart grid

A novel smart method for state estimation in a smart grid using smart meter data