My name is Leonor Fernandes, and I am a Machine Learning Engineer with a Master's degree in Bioengineering. I specialize in developing and deploying AI-driven solutions with a strong focus on machine learning and deep learning (including CNNs, Transformers, VAEs, and GANs). I am proficient in Python and PyTorch, with broad experience in data science, particularly in signal and image processing and analysis. I'm passionate about applying state-of-the-art AI research to projects with real-world impact.

Leonor Fernandes

My name is Leonor Fernandes, and I am a Machine Learning Engineer with a Master's degree in Bioengineering. I specialize in developing and deploying AI-driven solutions with a strong focus on machine learning and deep learning (including CNNs, Transformers, VAEs, and GANs). I am proficient in Python and PyTorch, with broad experience in data science, particularly in signal and image processing and analysis. I'm passionate about applying state-of-the-art AI research to projects with real-world impact.

Available to hire

My name is Leonor Fernandes, and I am a Machine Learning Engineer with a Master’s degree in Bioengineering. I specialize in developing and deploying AI-driven solutions with a strong focus on machine learning and deep learning (including CNNs, Transformers, VAEs, and GANs).

I am proficient in Python and PyTorch, with broad experience in data science, particularly in signal and image processing and analysis. I’m passionate about applying state-of-the-art AI research to projects with real-world impact.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Fluent
Portuguese
Fluent
French
Beginner

Work Experience

AI Research Engineer Intern at INESC TEC
July 1, 2025 - July 1, 2025
Trained and optimized ML models (Logistic Regression, XGBoost, Decision Trees) for diabetic retinopathy detection. Designed deep learning pipelines using PyTorch and HuggingFace to analyze retinal fundus images. Researched and implemented autoencoders, VAEs, and GANs to generate synthetic images disentangled from patient attributes. Researched and implemented fairness metrics and visualization techniques to evaluate model bias, establishing a framework to detect and mitigate unfair models.
Data Scientist Intern at Laboratory for Neuro- and Psychophysiology, KU Leuven
January 31, 2025 - January 31, 2025
Built and maintained scalable Python data pipelines for processing multi-gigabyte neural datasets. Applied signal cleaning, feature extraction, and dimensionality reduction to improve decoding accuracy. Developed Kalman filter-based real-time decoding simulations to assess neural activity patterns. Applied manifold alignment to enhance decoding stability across sessions and subjects, validated in simulations.

Education

Master's degree in Biooengineering, with a specialization in Biomedical Engineering at Faculty of Engineering, University of Porto
September 1, 2020 - July 21, 2025
Fundamental concepts of biology, data structures, programming, and signal processing. Focus on data analysis, ML, and AI algorithms applied to biomedical challenges.
BSc in Bioengineering - Biomedical Engineering at Faculty of Engineering of the University of Porto (FEUP)
September 1, 2020 - July 1, 2023
MSc in Bioengineering - Biomedical Engineering at Faculty of Engineering of the University of Porto (FEUP)
September 1, 2023 - July 1, 2025

Qualifications

C2 Proficiency - Cambridge English
December 1, 2020 - December 15, 2030

Industry Experience

Computers & Electronics, Manufacturing, Healthcare, Life Sciences, Software & Internet, Professional Services