Summary
Zhuang Liu is an Assistant Professor of Computer Science and a researcher with nine years of experience specializing in deep learning and computer vision, currently transitioning from Meta FAIR to Princeton. He led the development of widely used architectures such as DenseNet (CVPR Best Paper) and ConvNeXt, and focuses on model architectures, training dynamics, efficiency, and understanding, often challenging prevailing assumptions. His work spans vision, language, and multimodal models as well as dataset studies, and he favors simple, empirically driven approaches to reveal surprising behaviors in neural networks. Trained at Tsinghua and UC Berkeley, he combines top-tier academic rigor with hands-on industry research internships at Meta, Intel Labs, and Adobe, making his projects both theoretically informed and practically impactful.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of California, Berkeley
Exchange student Computer Science, Exchange student Computer Science at Cornell University
Bachelor's degree Computer Science (Yao Class), Bachelor's degree Computer Science (Yao Class) at Tsinghua University