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Lourdes-Tolotto/README.md

Hi, I’m Lourdes Tolotto 👋

Electronic Engineer and M.Sc. candidate in Artificial Intelligence at the University of Buenos Aires.

I work at the intersection of electronic engineering, signal processing, machine learning, and applied AI. My current interests include biomedical signal analysis, sleep staging, physiological data, and intelligent systems for real-world engineering problems.

🔬 Current Work

  • Developing a sleep staging pipeline using multichannel biomedical signals such as EEG, EOG, EMG, and ECG
  • Applying machine learning and deep learning models to physiological signal classification
  • Exploring signal preprocessing, feature extraction, model evaluation, and reproducible experimentation
  • Building projects related to electronic instrumentation, embedded systems, and data-driven engineering

🧠 Research Interests

  • Biomedical signal processing
  • Machine learning and deep learning
  • Sleep analysis and physiological data
  • Intelligent electronic systems
  • Applied AI for healthcare and engineering
  • Pattern recognition and time-series analysis

🚀 Technical Stack

AI, Data & Signal Processing

Python · NumPy · Pandas · Scikit-learn · PyTorch · TensorFlow · Signal Processing · Time Series

Engineering

Electronic Instrumentation · Embedded Systems · ESP32 · Arduino · C/C++ · MATLAB

Tools

Git · GitHub · Jupyter · VS Code · Anaconda · Docker · Linux · Power BI

🎯 Current Goals

I am currently strengthening my research experience and exploring Ph.D. and research opportunities in artificial intelligence, biomedical signals, sensing technologies, and applied engineering.

📫 Contact

Pinned Loading

  1. Automatic-Sleep-Staging Automatic-Sleep-Staging Public

    Automatic Sleep Stage Classification Using Deep Learning on Multichannel Biomedical Signals (EEG, EOG, and EMG)

    Jupyter Notebook

  2. Lourdes-Tolotto Lourdes-Tolotto Public

    Electronic Engineer | MSc in AI | Focused on signal processing & applied machine learning

  3. storm-events-damage-prediction storm-events-damage-prediction Public

    End-to-end machine learning project for NOAA Storm Events damage severity prediction, with temporal validation, leakage control, model comparison and LightGBM optimization.

    Jupyter Notebook