May 2024
This project aims to develop a chemistry-inspired diffusion model with non-differentiable guidance for generating novel molecules with desired properties while enhancing molecular stability.
October 2023
This project aims to develop a hierarchical machine learning model for predicting the stability of emulsions and to use it to develop sustainable formulations with greener chemicals.
July 2023
This aim of this project is to leverage machine learning and automated lab technologies to autonomously determine Hansen Solubility Parameters (HSPs) in a closed-loop fashion.
May 2023
This project aims to develop a physics-inspired machine learning model for predicting the viscosity of complex fluids and to use it to aid in the formulation design process.