Jian Tang

Jian Tang is a leading researcher in graph neural networks and their application to drug discovery and molecular design. His work has developed novel architectures for learning molecular representations that capture 3D structure and enable property prediction. Tang's research advances AI methods for understanding molecular interactions relevant to cancer therapeutics.

唐建是图神经网络及其在药物发现和分子设计应用方面的领先研究者。他的工作开发了学习分子表示的新架构，捕获3D结构并实现属性预测。唐的研究推进了理解与癌症治疗相关的分子相互作用的AI方法。