🔭 I’m working on machine learning and data mining, particularly on Reinforcement Learning (RL) and Data-centric AI

😄 I love developing open-source projects. I’m looking forward to collaborate on any fun projects.

🤔 I have made a YouTube video to share my journey of open-source projects.

Project	Stars	Resources
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning		ICML'21 Paper | Demo | 知乎 | Video | Blog
RLCard: A Toolkit for Reinforcement Learning in Card Games		IJCAI'20 Paper | Demo | 知乎 | Video | Blog
TODS: Automated Time-series Outlier Detection System		AAAI'21 Paper | Blog | Video
FinGPT: Democratizing Internet-scale Data for Financial Large Language Models		Paper | Website
Awesome Data-centric AI Resources		Survey Paper | Perspective Paper | 知乎 | Blog
Awesome Game AI Resources on Multi-agent Learning
RLCard-Showdown: Frontend for DouZero and RLCard		Demo
AutoVideo: An Automated Video Action Recognition System		IJCAI'22 Paper | Blog | Video
PyODDS: An End-to-end Outlier Detection System		WWW'20 Paper
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning		Paper | 知乎
Understanding Different Design Choices in Training Large Time Series Models		Paper
Towards Similarity-Aware Time-Series Classification		SDM'22 Paper
BED: A Real-Time Object Detection System for Edge Devices		CIKM'22 Best Demo Paper | Video
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments		ICLR'21 Paper
Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning		ICDM'20 Paper
DreamShard: Generalizable Embedding Table Placement for Recommender Systems		NeurIPS'22 Paper
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research		Paper | Demo | Video
AutoShard: Automated Embedding Table Sharding for Recommender Systems		KDD'22 Paper
NeuroShard: Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models		MLSys'23 Paper
Towards Automated Over-Sampling for Imbalanced Classification		CIKM'22 Paper