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Mr. Godfrey Oise | Environmental Biophotonics Research | Best Researcher Award

Ph. D Student at University of Benin, Nigeria

Oise Godfrey Perfectson is a Ph.D. candidate, research assistant, and assistant lecturer in Computer Science at the University of Benin, Nigeria. With a solid foundation in deep learning and software engineering, he has developed notable expertise through teaching and research, with a focus on innovation for sustainable e-waste management and environmental protection. His commitment to education and research has contributed significantly to advancements in deep learning applications.

Profile

Google Scholar

Strengths for the Award šŸŒŸ

Oise has demonstrated expertise in applying deep learning to real-world environmental challenges, particularly in e-waste management. His innovative approach addresses both sustainability and public health, making his work impactful on multiple levels.

With 12 publications in indexed journals, Oise shows a consistent commitment to research and an ability to contribute actively to his field. His work has been recognized and cited, establishing his research as influential within computer science and sustainable environmental solutions.

Oiseā€™s work is not purely theoretical; it targets practical applications of AI in waste management, with direct implications for environmental safety. This applied focus adds significant value to his profile, making him a strong candidate for the Best Researcher Award.

Beyond research, Oise has taken on roles that positively impact his academic community. Through his teaching, mentorship, and involvement in community outreach, he demonstrates a commitment to knowledge sharing and student growth.

Education šŸŽ“

Oise holds a Masterā€™s degree in Computer Science from the University of Benin (2022) and is currently pursuing his Ph.D. in the same field. Building on his academic journey from a Bachelorā€™s in Computer Science (2019), he has also enhanced his skills through certifications in Python and R programming, keeping pace with evolving industry demands.

Experience šŸ’¼

Oise has been involved in academia and research at the University of Benin since 2019. As a sandwich lecturer and research assistant with Professor Konyehaā€™s lab, he has played a key role in teaching, mentoring, and collaborative research. His teaching portfolio includes courses like Introduction to Software Engineering and Digital Design and Microprocessor, enriching the academic experience of his students while making impactful contributions to departmental projects.

Research Interests šŸ”

Oiseā€™s research is rooted in deep learning, with a keen focus on sustainable applications in e-waste management. His innovative work seeks to address environmental and public health concerns by applying artificial intelligence to optimize waste handling. His expertise in software engineering and deep learning fuels his contributions to both theoretical and practical advancements.

Awards and Recognitions šŸ†

Oise is recognized within his academic circle for his dedication to research and innovation. His nomination for the Best Researcher Award reflects his efforts in driving meaningful impact through deep learning applications in environmental science, demonstrating his potential for significant contributions to both academia and society.

Publications šŸ“š

Oise has authored numerous articles published in esteemed journals, with 12 publications in indexed journals to his name. His research on deep learning for e-waste management, published in journals such as the International Transactions on Electrical Engineering and Computer Science, highlights his focus on sustainable development. A few of his prominent publications include:

Optimizing business intelligence system using big data and machine learning

  • Authors: GG James, GP Oise, EG Chukwu, NA Michael, WF Ekpo, PE Okafor
  • Year: 2024

A Framework on E-Waste Management and Data Security System

  • Author: OG Perfectson
  • Journal: A Framework on E-Waste Management and Data Security System
  • Year: 2023

Harnessing Deep Learning for Sustainable E-Waste Management and Environmental Health Protection

  • Authors: GP Oise, S Konyeha
  • Year: 2024

A Web Base E-Waste Management and Data Security System

  • Author: G Oise
  • Journal: RADINKA Journal of Science and Systematic Literature Review
  • Year: 2023

E-Waste Management through Deep Learning: A Sequential Neural Network Approach

  • Authors: G Oise, S Konyeha
  • Journal: FUDMA Journal of Sciences
  • Year: 2024

A Proposed model for Decongesting Correctional Facilities in Edo State

  • Author: GO Perfectson
  • Journal: EIKI Journal of Effective Teaching Methods
  • Year: 2023

Deep Learning System for E-Waste Management

  • Authors: O Godfrey, S Konyeha
  • Conference: The 3rd International Conference on Electronic Processes
  • Year: 2024

Systematic Literature Review on Machine Learning, Deep Learning, and IoT-based Model for E-Waste Management

  • Authors: GP Oise, OJ Akpowehbve
  • Journal: International Transactions on Electrical Engineering and Computer Science
  • Year: 2024

Deep Learning for Effective Electronic Waste Management and Environmental Health

  • Authors: GP Oise, K Susan
  • Year: 2024

Oiseā€™s publications are frequently cited, reflecting the significance of his contributions to both the academic and applied fields of deep learning and environmental sustainability.

Conclusion šŸ”—

Oise Godfrey Perfectson is a commendable candidate for the Best Researcher Award due to his impactful research on sustainable e-waste management through deep learning, combined with a dedication to student mentorship and academic growth. By continuing to broaden his collaborative and funding reach, Oise has the potential to become a leader in his field. His current contributions reflect a genuine dedication to using AI for societal benefit, which aligns well with the objectives of the Best Researcher Award.

Godfrey Oise | Environmental Biophotonics Research | Best Researcher Award

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