Alain Bernard Djimeli Tsajio | Apprentissage Machine (IA) | Best Researcher Award

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Prof. Alain Bernard Djimeli Tsajio | Apprentissage Machine (IA) | Best Researcher Award

Senior lecturer at University of Dschang, Cameroon.

Prof. Alain Bernard Djimeli Tsajio is a physicist, AI researcher, and telecommunications expert specializing in computer vision, machine learning, and cybersecurity. He holds a Ph.D. in Electronics from the University of Dschang and has over 20 years of experience in academia and research. As a faculty member at IUT Fotso Victor, University of Dschang, he has significantly contributed to curriculum development, student mentorship, and applied research in artificial intelligence. His work has been published in high-impact journals, and he actively collaborates on international research projects in AI-driven diagnostics, wireless networks, and intelligent security systems.

Publication Profile

Orcid

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Educational Details

  • Ph.D. in Physics (Electronics), 2016 – University of Dschang, Cameroon

  • Diplôme d’Études Approfondies (DEA) in Physics (Electronics), 2005 – University of Yaoundé I, Cameroon

  • Maîtrise in Physics (Electronics), 2003 – University of Yaoundé I, Cameroon

  • Licence in Physics, 2000 – University of Yaoundé I, Cameroon

  • Baccalauréat C, 1995 – Lycée Classique de Bangangté, Cameroon

Professional Experience

Prof. Djimeli Tsajio is a Senior Lecturer and Researcher in Telecommunications and Networks at the IUT Fotso Victor, University of Dschang, Cameroon. Since 2005, he has been responsible for course coordination, student mentoring, and curriculum development. His teaching expertise covers a broad range of topics, including:

  • Multimedia Protocols and Quality of Service

  • Wireless Networks and Emerging Technologies

  • Cybersecurity and Artificial Intelligence

  • Information Theory and Cryptography

  • Telecommunication Protocols and High-Speed Networks

He has also served as an instructor at the CISCO Networking Academy, a guest lecturer at multiple universities, and a thesis advisor for Master’s and Ph.D. students in AI and Cybersecurity. His administrative contributions include student academic counseling, exam grading, and research program coordination.

Research Interest

  • Precision Agriculture (disease detection in plants)

  • Medical Diagnostics (breast cancer detection, leukocyte counting)

  • Network Security and Cybersecurity

  • AI-Based Intelligent Agents

Top Noted Publication

  • Solitons and other solutions of the nonlinear fractional Zoomeron equation

    • Authors: E. Tala-Tebue, Z. I. Djoufack, A. Djimeli-Tsajio, A. Kenfack-Jiotsa

    • Journal: Chinese Journal of Physics

    • Volume: 56 (3), Pages: 1232-1246

    • Year: 2018

    • Citations: 26

    • Summary: This paper presents soliton solutions and other exact solutions to the nonlinear fractional Zoomeron equation, leveraging advanced mathematical techniques in nonlinear wave dynamics and fractional calculus.

  • Improved detection and identification approach in tomato leaf disease using transformation and combination of transfer learning features

    • Authors: A. B. Djimeli-Tsajio, N. Thierry, L. T. Jean-Pierre, T. F. Kapche, P. Nagabhushan

    • Journal: Journal of Plant Diseases and Protection

    • Volume: 129 (3), Pages: 665-674

    • Year: 2022

    • Citations: 14

    • Summary: This study introduces an AI-based method for plant disease detection, utilizing transfer learning and feature transformation techniques to improve tomato leaf disease identification.

  • Quantum breathers associated with modulational instability in 1D ultracold boson in optical lattices involving next-nearest neighbor interactions

    • Authors: Z. I. Djoufack, E. Tala-Tebue, F. Fotsa-Ngaffo, A. B. Djimeli-Tsajio, F. Kapche-Tagne

    • Journal: Optik

    • Volume: 164, Pages: 575-589

    • Year: 2018

    • Citations: 13

    • Summary: This work explores quantum breathers and modulational instability in ultracold bosonic systems under optical lattice constraints, contributing to quantum physics and nonlinear dynamics.

  • Formalization method of the UML statechart by transformation toward Petri Nets

    • Authors: T. Noulamo, E. Tanyi, M. Nkenlifack, J. P. Lienou, A. Djimeli

    • Journal: IAENG International Journal of Computer Science

    • Volume: 45 (4), Pages: 32

    • Year: 2018

    • Citations: 8

    • Summary: This paper focuses on software modeling and verification, proposing a methodology for transforming UML statecharts into Petri Nets for improved formal verification of software systems.

  • Analysis of interest points of curvelet coefficients contributions of microscopic images and improvement of edges

    • Authors: A. Djimeli, D. Tchiotsop, R. Tchinda

    • Journal: arXiv preprint

    • Year: 2013

    • Citations: 8

    • Summary: This study investigates curvelet transform techniques for microscopic image analysis, improving edge detection in biological and medical imaging.

Conclusion

Prof. Alain Bernard Djimeli Tsajio is a strong candidate for the Best Researcher Award, given his significant contributions to AI, cybersecurity, and telecommunications. His work in AI-driven plant disease detection and medical diagnostics highlights both technical excellence and real-world impact. Strengthening his global presence, industry partnerships, and citation impact could further solidify his position as a leading researcher in his field.

 

Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

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Ms. Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

Software Engineer at Skyline Software Solutions, India

Ms. Swati Patel is an accomplished Data Analyst and Software Developer with extensive expertise in data science, machine learning, and software engineering. She has contributed significantly to academic research, publishing 8 journal papers, 2 IEEE conference papers, and 5 books on topics ranging from software security to predictive analytics. With strong analytical skills and a track record of developing efficient workflows and impactful applications, she has consistently delivered data-driven solutions for business optimization and research innovation.

Publication Profile

Google Scholar

Educational Details

Ms. Swati Patel holds a Master of Science in Advanced Computing Technologies from Birkbeck, University of London (2022-2023), where her projects included Principal Component Analysis on the Pima Indians Diabetes Dataset and predicting DDoS attacks using Darknet Time-Series data. She earned a Master’s degree in Computer Science from SES’s R. C. Patel Institute of Technology (NMU, India, 2012-2014), completing her thesis on software birthmark-based theft detection of JavaScript programs. Her Bachelor’s degree in Computer Engineering was completed at PSGVPM’s D. N. Patel College of Engineering, Shahada (NMU, India, 2008-2012), where she developed an Online Voting System using ASP.NET and SQL.

Professional Experience

Swati Patel is a Data Analyst and Entrepreneur with proven expertise in designing and optimizing workflows, data visualization, and software development. She served as a Data Analyst at SSP Group PLC, UK (2023-2024), where she created interactive Power BI dashboards to analyze sales data, optimized EPOS systems for data accuracy, and reduced data processing time by 30% through SQL optimization. As an entrepreneur, she successfully led Skyline Software Solutions (2014-2022), developing over 35 applications in Java, .NET, and other technologies. She managed end-to-end project execution, providing high-quality software solutions to diverse industries.

Research Interest

Swati’s research focuses on applied machine learning, natural language processing, and predictive modeling. She is particularly interested in statistical methods for data anomaly detection, speech-based health diagnostics, and secure systems in computing environments. Her work also extends to innovative clustering techniques for theft detection in software and dimensionality reduction in large datasets.

Author Metrics

  • Publications: 2 IEEE papers, 8 journal papers, 5 books.
  • Key Topics: Data science, machine learning, NLP, secure computing systems, predictive analytics.
  • Notable Works:
    • “A Review on Statistical Analysis-Based Approaches for Data Poison Detection Using Machine Learning.”
    • “Automated Depression Assessment from Speech Signals Using Pitch and Energy Features.”
    • “Long Short-Term Memory and Gated Recurrent Unit Networks for Accurate Stock Price Prediction.”
    • Books: COVID-19 Data Analysis for the United Kingdom and Data Exploration and Machine Learning using R.

Publication Top Notes

  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Frequent Subgraph Mining
    • Authors: S.J. Patel, T.M. Pattewar
    • Conference: 2014 International Conference on Embedded Systems (ICES)
    • Pages: 63–68
    • Citations: 9
    • Year: 2014
    • Summary: This paper presents a novel method for detecting software theft in JavaScript programs using software birthmarks. The approach employs agglomerative clustering and frequent subgraph mining to identify similarities between programs, aiding in theft detection.
  • K-Means Clustering Algorithm: Implementation and Critical Analysis
    • Author: S. Patel
    • Publisher: Scholars’ Press
    • Citations: 8
    • Year: 2019
    • Summary: This publication provides an in-depth exploration of the K-means clustering algorithm, including its implementation and a critical analysis of its efficiency and limitations in clustering diverse datasets.
  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Improved Frequent Subgraph Mining
    • Authors: S. Patel, T. Pattewar
    • Conference: 2014 International Conference on Advances in Electronics, Computers, and Communications
    • Citations: 7
    • Year: 2014
    • Summary: This paper builds upon earlier research by introducing an improved method for frequent subgraph mining, enhancing the detection accuracy of JavaScript program theft through advanced birthmark-based techniques.
  • Software Birthmark for Theft Detection of JavaScript Programs: A Survey
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJAFRC (International Journal of Advanced Foundation and Research in Computers)
    • Volume: 1, Issue 2, Pages: 29–38
    • Citations: 2
    • Year: 2014
    • Summary: This survey reviews existing methods for detecting software theft in JavaScript programs, with a focus on software birthmark techniques. It outlines challenges, solutions, and future research directions.
  • Emerging Trends in Computer Technology (NCETCT)
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJCA (International Journal of Computer Applications)
    • Conference Issue: NCETCT, Number 1
    • Year: 2014
    • Summary: This conference paper discusses advancements in computer technology with a focus on software security. It explores the use of software birthmarks as a means of detecting and preventing intellectual property theft in programming.

Conclusion

Ms. Swati Patel is a highly qualified and deserving candidate for the Best Researcher Award. Her combination of academic excellence, impactful research, and real-world contributions to artificial intelligence and software engineering set her apart as an innovative thinker. To maximize her potential and visibility, she could focus on strengthening her citation impact, pursuing international collaborations, and contributing to higher-impact conferences. Overall, her track record reflects dedication, skill, and the ability to drive meaningful advancements in her field.