Phd Scholar- Computational Science & Engineering
My research focuses on developing computational tools and data-driven approaches for the early identification of newly emerging risk chemicals (NERCs). I work at the intersection of computational science, data science, and environmental toxicology, applying text mining, natural language processing (NLP), machine learning (ML), and image recognition to extract and analyze chemical information from scientific and patent literature. The aim of my research is to improve the early detection and surveillance of NERCs and support the development of more effective early warning system (EWS).
Teaching in Chemometrics (multivariate analysis and design of experiments) and Computational Chemistry (QSAR modelling).