Keyu Tian
硕士研究生 at 北京大学
Haidian District, Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolKeyu Tian is an AI researcher and incoming Ph.D. student with eight years of experience focused on multimodal perception, video generation, self-supervised learning, and reinforcement learning. Currently a master’s candidate at Peking University, Keyu has held research internships at ByteDance AI Lab, SenseTime, and a remote collaboration with Oxford’s Torr Vision Group, blending industry-scale experimentation with academic rigor. They specialize in open-ended generative and RL problems for video and multimodal AI, regularly moving ideas from papers to prototypes in production-adjacent research environments. Based in Haidian, Beijing, Keyu pairs deep technical breadth with practical impact—recent work at ByteDance’s VC team targeted scalable video-centric models. An underrated strength is their consistent cross-institutional collaboration experience, enabling fast iteration across research labs and applied teams.
7 years of coding experience
Bachelor Software Engineering, Bachelor Software Engineering at Beihang UniversityMaster CS, Master CS at Peking University
Github Skills (55)
sparse10
convolutional-neural-networks10
ssl10
hierarchical10
python10
pre-trained-model10
re-identification10
pretrain10
machine-learning10
voc10
deep-learning10
self-supervised-learning10
gpu10
kitti-dataset10
object-detection10
Programming languages (4)
Github contributions (5)
Ke-Coding/Data-Structure-Cpp11
Mar 2019 - Jul 2019
Contributions:78 commits, 23 pushes, 1 branch in 3 months
keyu-tian/SparK
Jan 2023 - Mar 2023
[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"
Contributions:2 releases, 16 commits, 109 pushes in 2 months
bertconvnethierarchicalsparsevisual-recognition
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