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I am a first-year Ph.D. student at University of Pennsylvania, working with Prof. Lingjie Liu and Prof. Kostas Daniilidis. I complete my Master of Science degree from UC Berkeley, advised by Prof. Trevor Darrell , where I work on computer vision and representation learning. Before that, I was an undergraduate student at UC Berkeley, majoring in Computer Science and Applied Mathematics. I also interned at Twitter as a machine learning engineer, and Oneflow as a machine learning engineer. I was closely mentored by Dr. Zhuang Liu and Ph.D. candidate Ruiqi Zhong at UC Berkeley. They are primarily reasons why I dived into research. Email / Google Scholar / Twitter / Github / Wechat |
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Zhuang Liu*, Zhiqiu Xu*, Joseph Jin, Zhiqiang Shen, Trevor Darrell (* equal contribution) ICML, 2023 arXiv We propose early dropout and late dropout. Early dropout helps underfitting models fit the data better and achieve lower training loss. Late dropout helps improve the generalization performance of overfitting models. |
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Zhuang Liu, Zhiqiu Xu, Hung-ju Wang, Trevor Darrell, Evan Shelhamer ICLR, 2022 arXiv Our full method, named Anytime Dense Prediction with Confidence (ADP-C), achieves the same level of final accuracy with HRNet-w48, and meanwhile significantly reduces total computation. |
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Just like every other field in human society, the flourishing academic community is reliant on passing the torch of knowledge. If you are interested in computer vision and want to chat with me, please don't hesitate to reach out. Here is a list of students I have mentored. One of them said I was a legendary mentor, and let's trust his judgement for this time. |
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Reviewer for ICCV, NeuRIPS. |
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Website design from Jon Barron Borrowed from Ruiqi Zhong |