I am currently a Ph.D. student at Peking University supervised by Prof. Zhouchen Lin. Previously I obtained my B.S. degree in computer science and technology and B.S. degree in psychology from Peking University in 2020. Curriculum Vitae.

My research interests lie in machine learning, including deep learning, optimization, as well as their application in computer vision, image processing, and intersection with cognitive science.

In the summer 2019, I was a visiting student at CCVL (Computational Cognition, Vision, and Learning) lab in Johns Hopkins University, supervised by Prof. Alan Yuille.

From Sep. 2019 to Jun. 2020, I was a research intern at Microsoft Research Asia Machine Learning Group led by Dr. Tie-Yan Liu.


Publications / Preprints

Yaolong Wang; Mingqing Xiao; Chang Liu; Shuxin Zheng; Tie-Yan Liu. Modeling Lost Information in Lossy Image Compression. [arXiv]

Mingqing Xiao; Shuxin Zheng; Chang Liu; Yaolong Wang; Di He; Jiang Bian; Guolin Ke; Zhouchen Lin; and Tie-Yan Liu. Invertible Image Rescaling. ECCV 2020 (Oral, 2%). [arXiv] [code].

Mingqing Xiao; Adam Kortylewski; Ruihai Wu; Siyuan Qiao; Wei Shen; and Alan Yuille. 2019. TDMPNet: Prototype Network with Recurrent Top-Down Modulation for Robust Object Classification under Partial Occlusion. ECCV 2020 Workshop. [link].

Jia Li; Mingqing Xiao; Cong Fang; Yue Dai; Chao Xu; and Zhouchen Lin. Training Deep Neural Networks by Lifted Proximal Operator Machines. IEEE Trans. Pattern Analysis and Machine Intelligence, 2020. [link].