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fotsingk/README.md

Welcome to My Portfolio

About Me

Hello! I'm Fotsing Kuetche, a dedicated educator and researcher specializing in machine learning and applied artificial intelligence. With a solid background in science and technology, I am passionate about teaching, research, and innovation. I am currently seeking consultancy and machine learning researcher roles to further apply my skills and contribute to impactful AI-driven projects.

Skills

  • Pedagogy and Adaptation: Effective at tailoring complex concepts for diverse audiences.
  • Team Spirit and Collaboration: Strong collaborative skills in team settings.
  • Leadership and Evaluation: Proven experience in leading projects and evaluating research.
  • Programming Languages: Proficient in MatLab/Simulink, Python, Fortran.
  • Biomedical Signal Processing: Expertise in analyzing and processing biomedical signals.
  • Meta-Heuristics and Optimization: Skilled in developing optimization algorithms.
  • Machine Learning: In-depth knowledge of machine learning techniques and applications.
  • Applied Artificial Intelligence: Experience with AI solutions in various domains.
  • Renewable Energy: Knowledgeable in renewable energy technologies and applications.

Experience

Teaching & Research Assistant, The University of Ngaoundere

Oct 2023 – Present

  • Led tutorials on signal processing, basic electronics, programming languages, and code debugging.
  • Assisted and supervised graduate students in laboratory settings.
  • Conducted research on AI models for telemedicine applications.

Reviewer, Engineering Application of Artificial Intelligence

2023 – Present

  • Evaluated journal submissions based on quality, completeness, and accuracy of research.

Publications

  1. K. Fotsing, A. Noura, P. Ntsama Eloundou, C. Welba, T. Simo (2023). Signal Quality Indices Evaluation for Robust ECG Signal Quality Assessment Systems. Biomed. Phys. Eng. Express.

  2. K. Fotsing, A. Noura, P. Ntsama Eloundou, T. Simo (2023). Simple, Efficient, and Generalized ECG Signal Quality Assessment Method for Telemedicine Applications. Informatics in Medicine Unlocked, 42, 101375.

  3. K. Fotsing, A. Noura, P. Ntsama Eloundou, C. Welba, T. Simo (2024). DeepAF: A Multi-task Deep Learning Model for Arrhythmias Detection at Resource-Constrained Mobile Devices. In: Safe, Secure, Ethical, Responsible Technologies and Emerging Applications, SAFER-TEA 2023. Springer, Cham.

  4. K. Fotsing, A. Noura, P. Ntsama Eloundou, T. Simo (In Revision). ecgScorer: A Matlab Toolbox to Assess ECG Signal Quality for Telemedicine Applications. Software-x.

  5. Fotsing Kuetche, Ntsama Eloundou .P, Noura Alexendre (2024). Quality Assessment and Noise Detection using Convolution Neural Network for Unsupervised Electrocardiogram (ECG) Analysis Systems. Scientific Days: Fundamentals and Applied Research at the Service of Sustainable Development, Maroua, Cameroon.

Contact

Feel free to reach out to me through the following platforms:

Thank you for visiting my portfolio!

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Popular repositories Loading

  1. ECG-Denoising-with-wavelet- ECG-Denoising-with-wavelet- Public

    Denoising of ECG with wavelet

    MATLAB 3

  2. PigmaDatatest PigmaDatatest Public

    Python

  3. ecg-classification ecg-classification Public

    Forked from lxdv/ecg-classification

    ECG Arrhythmia classification using CNN

    Jupyter Notebook

  4. coding-practice coding-practice Public

    Forked from sandgate-dev/coding-practice

    A notebook and a place to gather my thoughts regarding coding

  5. TFLClassify TFLClassify Public

    Forked from hoitab/TFLClassify

    TensorFlow Lite code lab for implementing a custom flower classifier.

    Kotlin

  6. MobileNet-1D-2D-Tensorflow-Keras MobileNet-1D-2D-Tensorflow-Keras Public

    Forked from Sakib1263/MobileNet-1D-2D-Tensorflow-Keras

    Supported Models: MobileNet [V1, V2, V3_Small, V3_Large] (Both 1D and 2D versions with DEMO, for Classification and Regression)

    Jupyter Notebook