🔍 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
