Researcher

Jin Da Tan graduated with a bachelor’s degree in Chemistry from the National University of Singapore in 2019 and earned his PhD at A*STAR IMRE under Kedar Hippalgaonkar and Balamurugan Ramalingam. Tan’s research interests include machine learning (ML) and its intersectionality with automation, chemistry and other domains.

At A*STAR, Tan’s research explored the application of ML techniques to enhance chemical synthesis, focusing on the prediction and optimisation of experimental outcomes, as well as the generative design of small organic molecules. His key projects included the development of predictive models for entire molecular weight distributions during polystyrene flow reactor synthesis, as well as the exploration and refinement of the diketopyrrolopyrrole molecular core; an approach which enabled the validation and discovery of novel non-fullerene acceptors for organic photovoltaic material design.

Transitioning from academia to the finance industry, Tan leveraged his programming, machine learning and problem-solving expertise to tackle complex data-driven challenges, including the building of predictive ML models tailored to the field. Today, he continues to explore innovative applications of artificial intelligence in data analysis and decision-making.