Experience

Publications

  • Fractional Fourier Transform, Signal Processing, and Uncertainty Principles
    Study of Heisenberg-type and related uncertainty principles for the fractional Fourier transform (FrFT), with applications in signal processing and numerical experiments using MATLAB.
    Circuits, Systems & Signal Processing, 42, 892–912 (2022). Z. Aloui, K. Brahim.
  • Time–Frequency Localization for the Fractional Fourier Transform in Signal Processing and Uncertainty Principles
    Analysis of time–frequency localization properties in the FrFT domain, with a focus on compression of different signal types and on qualitative and quantitative uncertainty principles.
    Circuits, Systems & Signal Processing, 40, 4924–4945 (2021). Z. Aloui, K. Brahim.
  • Some Random Fourier Matrices and Their Singular Values
    Investigation of random Fourier matrices and their singular values, with applications to dimensionality reduction techniques used in machine learning, including relations to principal component analysis (PCA).
    Journal of Mathematical Analysis and Applications, 508, Article 125891 (2022). Z. Aloui, A. Bonami.
  • Physiology-Informed Neural Network for Continuous Cuffless Blood Pressure Waveform Measurement
    This study introduces a physiology-informed, data-driven modeling framework for continuous cuffless blood pressure (BP) waveform estimation. The method is based on a nonlinear autoregressive model with exogenous inputs (NARX) implemented using artificial neural networks and trained on subject-specific ECG and PPG signals. Three configurations are investigated, including a physiology-informed variant (NARXphysio) that links the estimated BP and PPG waveforms through a four-parameter sigmoidal function. Evaluated over a 6-hour recording in daily life conditions, the physiology-informed model maintains accurate BP estimation over time and improves performance across various BP ranges, even with a shorter training window.
    Z. Aloui, C. Landry.
    Submitted
  • Approximation of the Fourier Transform of a Generalized Gaussian Distribution and Estimation of Atmospheric Parameters
    Study of the influence of atmospheric media such as rain and fog on artificial vision systems for autonomous vehicles. The work develops algorithms to filter noisy data, ensure accurate obstacle detection, and adapt image-processing parameters in real time to improve safety and reliability.
    Z. Aloui, F. Dubeau.
    In preparation

Conferences, Presentations, and Posters

  • Neural Network Architecture Physiology-Informed for Continuous Blood Pressure Waveform Estimation
    Oral presentation – JSDOCC 2025, Sherbrooke, Canada – 05/2025
    Zaineb Aloui, Céderick Landry
  • Neural Network Architecture Physiology-Informed for Continuous Blood Pressure Waveform Estimation
    Oral presentation ( Poster ) – BHI Colloquium, Atlanta, USA – 10/2025
    Zaineb Aloui, Céderick Landry
  • Neural Network Architecture Physiology-Informed for Continuous Blood Pressure Waveform Estimation
    Poster presentations – Montréal (06/2025), Sherbrooke (06/2025), Sherbrooke (03/2025)
    Zaineb Aloui, Céderick Landry
  • Random Fourier Matrices and Their Singular Values
    Poster presentation – University of Sherbrooke, (2023)
    Zaineb Aloui
  • Fractional Fourier Transform and Uncertainty Principles
    Poster presentation – University of Sherbrooke, (2023)
    Zaineb Aloui
  • Fractional Fourier Transform and Uncertainty Principles
    Oral presentation – JAMA 2018, Tunisia – 12/2018
    Zaineb Aloui, Kamel Brahim
  • Qualitative Uncertainty Principles: Morgan and Cowling–Price Theorems
    Oral presentation – JSMD 2019, Tunisia – 11/2019
    Zaineb Aloui, Kamel Brahim
  • Other Scientific Conferences & Academic Events
    • Colloquium of the Tunisian Mathematical Society – 03/2018
    • OPSF Summer School, Faculty of Sciences of Tunis – 06/2018
    • Harmonic Analysis and Data Science Conference, FST – 12/2018
    • Harmonic Analysis and Data Science Conference, FST – 11/2019
    • Harmonic Analysis and Spectral Theory Conference, FST – 12/2021
    • Mathematics Conference, University of Montreal – 12/2022
    • Mathematics Conference, University of Ottawa – 05/2023
    • Mathematics Conference, University of Montreal – 06/2023
    • Mathematics Conference, University of Montreal – 12/2023

    • Research and Professional Experience

    • Postdoctoral Researcher – Machine Learning
      University of Sherbrooke, Centre de Recherche sur le Vieillissement
      Development of algorithms for continuous cuffless blood pressure monitoring using smartwatch sensors.
      Preprocessing and analysis of biometric signals.
      Intelligent models for real-time cardiovascular monitoring and personalized alerts.
      Technologies: Python, Machine Learning, TensorFlow
    • Postdoctoral Researcher – Mathematics
      University of Sherbrooke, Faculty of Science — 2022 – 2023
      Mathematical analysis of atmospheric conditions affecting artificial vision for autonomous vehicles.
      Development of predictive models using Python and machine learning.
      Technologies: Python, ML, Applied Mathematics
    • Research Internship – Final Project
      University of Sherbrooke — 2022
      Analysis of atmospheric effects on embedded vision systems.
      Experimental design and development of image-processing algorithms.
      Technologies: Python, OpenCV, NumPy, Matplotlib
    • University Teacher in Mathematics & Python / Data Science Trainer
      University of Sherbrooke , QC (2022–2023)
      iTeam Tunisia (2021–2022)
      ISI Tunisia / University of Tunis El Manar (2019–2021)
      Training Centers – Tunisia (2020–2022)

      Preparation and organization of teaching material.
      Teaching: Analysis, Algebra, Numerical Analysis, Signal Processing, Matlab, Python, Machine Learning.
      Leading practical sessions and clarifying advanced computational and mathematical concepts.
      Evaluation of assignments/exams and academic support for students.
    • Python / Machine Learning / Full Stack Developer
      Various projects — 2020 – 2023
      Development of data-processing tools and analytical scripts.
      ML algorithms for classification and prediction.
      Creation of Python modules for academic and applied projects.
      Full Stack Developer (Angular & Spring Boot)

    Education and Professional Development

      PhD in Mathematics
      Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia
    • Master’s Degree in Applied Mathematics
      Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia
    • National Engineering Degree in Computer Science
      ESPRIT School of Engineering, Tunisia
      Final-year engineering project completed at the University of Sherbrooke (Canada).
    • Technical Certifications & IT Training
      • Spring & Angular Intensive Program, Bee Coders
      • Full Stack Certification – Angular & Java Spring Boot, Udemy
      • Data Science & Machine Learning Certification, Udemy
      • Python Programming Certification, Linux Academy
    • Soft Skills & Professional Training
      • Trainer Certification, MedSirat
      • Leadership Training, MedSirat
      • Public Speaking Program, MedSirat

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