Rachel (Xian) Liu

I believe the next frontier of Artificial Intelligence lies in its ability to reason about the physical world. As a former Associate Professor at Research Center for Eco-Environmental Sciences (RCEES), Chinese Academy of Sciences, I build AI systems that understand the fundamental rules of molecular interaction.

My journey began in pharmacy, where the inefficiency of traditional wet-lab experiments drove me to self-teach coding to automate data analysis. This sparked a passion for computation that led to a Ph.D. in Computer-Aided Drug Design (CADD) at the Shanghai Institute of Materia Medica and AI-based computational toxicology research at the RCEES.

For the past ten years at the RCEES, my research has focused on addressing pressing environmental health challenges through the integration of multi-modal deep learning. I lead interdisciplinary projects at the intersection of computational toxicology, AI-driven modeling, and risk governance. A central focus of my work is developing predictive frameworks that map structural signatures (molecular representations/spectral data) to biological responses and adverse outcomes, enabling intelligent identification of high-risk pollutants. I am also committed to delivering these solutions as live, accessible web services to support open scientific collaboration and decision-making.

Having moved to Silicon Valley to reunite with family, I am now looking for opportunities to join a forward-thinking research and engineering team.