Zixing Song

Zixing Song is a Research Fellow at Wolfson College and postdoctoral research associate in the Department of Engineering within the School of Technology at the University of Cambridge. His work focuses on advancing machine learning methodologies for interdisciplinary applications in molecular science and drug discovery.

He earned a Bachelor of Engineering in Computer Science from Southeast University, China, followed by a PhD in Computer Science and Engineering from The Chinese University of Hong Kong. His doctoral research pioneered label-efficient learning frameworks for graph-structured data with demonstrated applications across social science, financial science, and material science.

Current research centers on structure-based drug design using diffusion models and geometric machine learning to predict protein-ligand interactions. By integrating computational chemistry, generative AI, and molecular biology, Song develops symmetry-based inductive biases to optimize molecular structures for therapeutic applications, aiming to accelerate drug discovery while reducing traditional development costs and timelines.