About myself

I am a computational and biophysical chemist based in the UK, passionate about rational drug design. My career has been focusing on computational tools to tackle real-world challenges in drug discovery industry. My expertise lies in structure-based/computer-aided drug design, with a particular focus on novel chemical modalities for induced proximity.

I completed chemistry PhD at the University of Bristol (2022) following MRes at Imperial College London (2018), where I gained diverse experience across fields like synthetic medicinal chemistry, molecular modelling, quantum chemistry, and data science. I am skilled in techniques from physics-based simulations to machine learning statistics, to discover and develop potential drug candidates.

In my current role as CADD scientist in a biotech (2023-present), I've had the opportunity to develop modelling softwares and build QSAR pipelines for several drug discovery projects at different stages, including virtual screening and lead optimisations. I am always exploring new technologies like generative AI models and free energy calculations to explore chemical space and accelerate drug design efficiently. I believe in the power of interdisciplinary research and collaborate closely with medicinal chemists, structural biologists and DMPK experts in my daily work.

This blog is for sharing my perspective in fields of molecular modelling and cheminformatics.