Exploring the intersection of chemistry, biology, data science, and machine learning. I am building open-source tools for sustainable technologies and help scientists push the boundaries of their researches.
Open to collaborations on innovative projects.
- Molecular discovery with machine learning
- Photocatalysis and light-driven chemical reactions
- Photophysics and energy transfer mechanisms
- Biostimulants, green chemistry and data-driven insights for sustainable agriculture
- Artificial photosynthesis and renewable energy
A project aiming to enhance interactions with local models by automatically memorizing and summarizing past conversations to generate precise and context-aware prompts.
This project aims to develop an interface for the prediction of chemical reaction yields by combining molecular structure information, experimental conditions and ùachine learning models.
- Photocompounds Database (WIP)
A comprehensive database for artificial photosynthesis molecules and photocatalytic systems, with a focus on biomass valorization.
A project aiming to predict the properties, stability, and efficiency of photocompounds, using a homemade dataset.
An open-source repository for biostimulants and active compounds from bio-sources.
An AI-powered tool for predicting optimal biostimulant formulations, integrating chemical, biological, and agronomic data for maximum efficacy.
If you're working on projects related to sustainable chemistry, clean energy, or molecular innovation, feel free to reach out. I'd be happy to discuss with like-minded scientists !