Zichen Liu 刘梓辰

liuzc , sea.com | zichen , comp.nus.edu.sg

I'm a research engineer at Sea AI Lab, and a CS PhD student at National University of Singapore, advised by Prof. Lee Wee Sun and Dr. Lin Min.

I obtained my Bachelor degree in EE from NUS, advised by Dr. Feng Jiashi.

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Publication
clean-usnob Efficient Offline Policy Optimization with a Learned Model
Zichen Liu, Siyi Li, Wee Sun Lee, Shuicheng Yan, Zhongwen Xu
International Conference on Learning Representations (ICLR) 2023
pdf / code /
bibtex @inproceedings{liu2023rosmo, title={Efficient Offline Policy Optimization with a Learned Model}, author={Liu, Zichen and Li, Siyi and Lee, Wee Sun and Yan, Shuicheng and Xu, Zhongwen}, booktitle={International Conference on Learning Representations}, year={2023}, }

We investigate the deficiencies of MCTS in the offline MuZero algorithm and propose an efficient regularized improvement operator that achieves better sample- and compute-efficiency on the Atari benchmark.
clean-usnob EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine
Jiayi Weng, Min Lin, Shengyi Huang, Bo Liu, Denys Makoviichuk, Viktor Makoviychuk, Zichen Liu, Yufan Song, Ting Luo, Yukun Jiang, Zhongwen Xu, Shuicheng Yan
Advances in Neural Information Processing Systems (NeurIPS) 2022
pdf / code GitHub stars /
bibtex @inproceedings{weng2022envpool, author = {Weng, Jiayi and Lin, Min and Huang, Shengyi and Liu, Bo and Makoviichuk, Denys and Makoviychuk, Viktor and Liu, Zichen and Song, Yufan and Luo, Ting and Jiang, Yukun and Xu, Zhongwen and Yan, Shuicheng}, booktitle = {Advances in Neural Information Processing Systems}, title = {Env{P}ool: A Highly Parallel Reinforcement Learning Environment Execution Engine}, year = {2022} }

EnvPool provides ultrafast vectorized environments for RL. It allows solving Atari Pong in 5 minutes using PPO!
clean-usnob DANCE: A Deep Attentive Contour Model for Efficient Instance Segmentation
Zichen Liu, Jun Hao Liew, Xiangyu Chen, Jiashi Feng
Winter Conference on Applications of Computer Vision (WACV) 2021
pdf / code /
bibtex @inproceedings{liu2021dance, author = {Liu, Zichen and Liew, Jun Hao and Chen, Xiangyu and Feng, Jiashi}, title = {DANCE: A Deep Attentive Contour Model for Efficient Instance Segmentation}, booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, year = {2021}, }

We develop an efficient instance segmentation strategy based on the neural snake algorithm and attain SoTA performance on COCO among contour-based methods.

Open-source software
clean-usnob Model Serving made Efficient in the Cloud (MOSEC) GitHub stars

Mosec is a high-performance ML model serving framework built with a fast Rust web layer. It supports all different ML frameworks, such as Jax, PyTorch, TensorFlow, etc., with a super easy coding interface in Python. Dynamic batching and CPU/GPU pipelines are the core features that can fully exploit your computing machine.

Miscellanea

I like to play badminton and eat hotpot.

Credits