Liang-Chieh (Jay) Chen- Home Page
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Liang-Chieh Chen Email: lcchen at cs dot ucla dot edu |
About Me
I am currently a Research Scientist and Manager at TikTok with a focus on Computer Vision and Deep Learning.
I am widely recognized for my contributions to the DeepLab series (co-developed with George Papandreou): DeepLabv1, DeepLabv2, DeepLabv3, DeepLabv3+. Since December 2014, our introduced atrous convolution (also known as convolution with holes or dilated convolution) has become a foundational technique for dense prediction tasks.
Influential DeepLab derivatives include Auto-DeepLab, Panoptic-DeepLab (winning method of the Mapillary Vistas Panoptic Segmentation track at ICCV 2019, and top performer on Cityscapes leaderboards), Axial-DeepLab, ViP-DeepLab, MaX-DeepLab, and kMaX-DeepLab. Additionally, I am known for my collaborative work on MobileNetv2 and MobileNetv3, which have set new standards in efficient neural network design and search for mobile devices.
Prior to joining TikTok, I spent seven years as a Research Scientist at Google Research in Los Angeles (2016–2023). I earned my Ph.D. in Computer Science from the University of California, Los Angeles, in 2015, advised by Alan L. Yuille. I received my M.S. in Electrical and Computer Engineering from the University of Michigan, Ann Arbor.
Activities
Area Chair for ICCV 2019, 2025, CVPR 2020, 2023, 2024, 2025, ECCV 2020, 2024, NeurIPS 2022, 2024.
Action Editor for TMLR.
Reviewer for CVPR, ECCV, ICCV, NeurIPS.
Selected Recent Publications
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Randomized Autoregressive Visual Generation |
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MaskBit: Embedding-free Image Generation via Bit Tokens |
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Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models |
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An Image is Worth 32 Tokens for Reconstruction and Generation |