🔍 I am an AI Research Engineer with a strong foundation in deep learning models, and statistical learning. I specialize in building data-based algorithms for complex tasks, especially focusing on battery degradation modeling. I also have a deep interest in number theory applied to integer factoring algorithms.

⚡ My research and development interests include:

• Diffusion Models for generative tasks on time-series and scientific data.
• Variational Autoencoders (VAEs) for representation learning and anomaly detection.
• Transformer Architectures for long-range dependency modeling in time-series.
• Physics-Informed Machine Learning for better modeling of real-world systems.
• Battery Health Understanding/Forecasting using machine learning and AI-driven simulations.
• Signal processing using deep learning architectures.
• Experimenting with deep learning architecture and concepts.

🛠️ Technical Skills:

• Programming : Python (advanced), C, Java, Matlab, Julia, SQL
• Frameworks/Libraries : PyTorch, TensorFlow, Scikit-learn
• Machine Learning Expertise : Supervised, Unsupervised, Self supervised, and Generative Modeling
• Database Management : PostgreSQL, MongoDB
• DevOps & Tools : Linux, Git
• Scientific Computing : Statistical learning, number thoery algorithms

📚 Current Focus Areas:

• Building Deep learning models to estimate and predict key battery health indicators.
• Applying all sorts of model architectures on use-cases.
• Finalizing my number theory projects.

🤝 I'm looking to collaborate on projects related to:

• Battery lifecycle prediction ;
• Generative AI for scientific and industrial applications ;
• Put to the test AI models on real life tasks.

📫 Connect with me: basile.jezequel@gmail.com