{"id":23092539,"url":"https://github.com/daochenzha/daochenzha","last_synced_at":"2026-01-16T00:55:01.504Z","repository":{"id":133069972,"uuid":"491570923","full_name":"daochenzha/daochenzha","owner":"daochenzha","description":null,"archived":false,"fork":false,"pushed_at":"2024-06-26T23:00:20.000Z","size":51,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-02-09T06:44:05.054Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/daochenzha.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-05-12T15:31:48.000Z","updated_at":"2024-06-26T23:00:24.000Z","dependencies_parsed_at":"2024-12-16T21:34:50.159Z","dependency_job_id":"67085f51-8680-4556-a9d8-9904e22fc0bd","html_url":"https://github.com/daochenzha/daochenzha","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daochenzha%2Fdaochenzha","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daochenzha%2Fdaochenzha/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daochenzha%2Fdaochenzha/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daochenzha%2Fdaochenzha/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/daochenzha","download_url":"https://codeload.github.com/daochenzha/daochenzha/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247055431,"owners_count":20876187,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-16T21:34:26.120Z","updated_at":"2026-01-16T00:55:01.492Z","avatar_url":"https://github.com/daochenzha.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"### Hi there, I'm [Daochen Zha (查道琛 in Chinese)!](https://dczha.com/) 👋👋👋\n\n\u003c!---🌱 I’m currently a Machine Learning Engineer at Airbnb. I obtained my PhD from CS@Rice--\u003e\n\n🔭 I’m working on machine learning and data mining, particularly on Reinforcement Learning (RL) and Data-centric AI\n\n😄 I love developing open-source projects. I’m looking forward to collaborate on any fun projects.\n\n🤔 I have made a YouTube video to share [my journey of open-source projects](https://youtu.be/UBn9ks8fj80).\n\n:loudspeaker: News: Please check out our open-sourced [Large Time Series Model (LTSM)](https://github.com/daochenzha/ltsm)!\n\n:loudspeaker: News: Please check out our [data-centric AI survey](https://arxiv.org/abs/2303.10158) and [awesome data-centric AI resources](https://github.com/daochenzha/data-centric-AI)!\n\n\u003cimg src=\"https://github-readme-stats-git-masterorgs-github-readme-stats-team.vercel.app/api?username=daochenzha\u0026include_orgs=true\u0026show_icons=true\u0026bg_color=00000000\" /\u003e\n\n\n\n### Popular Projects\n\n| Project  | Resources |\n|---|---|\n| [Understanding Different Design Choices in Training Large Time Series Models](https://github.com/daochenzha/ltsm) | [Paper](https://arxiv.org/abs/2406.14045) \n| [DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research](https://github.com/ynchuang/DiscoverPath) | [Paper](https://arxiv.org/abs/2309.01808) \\| [Demo](http://www.discoverpath.top/) \\| [Video](https://youtu.be/xcDzBl7jp-s) |\n| [FinGPT: Democratizing Internet-scale Data for Financial Large Language Models](https://github.com/AI4Finance-Foundation/FinGPT) | [Paper](https://arxiv.org/abs/2307.10485) \\| [Website](https://ai4finance-foundation.github.io/FinNLP/) |\n| [OpenGSL: A Comprehensive Benchmark for Graph Structure Learning](https://github.com/OpenGSL/OpenGSL) | [Paper](https://arxiv.org/abs/2306.10280) \\| [知乎](https://zhuanlan.zhihu.com/p/642738341) |\n| [Awesome Data-centric AI Resources](https://github.com/daochenzha/data-centric-AI) | [Survey Paper](https://arxiv.org/abs/2303.10158) \\| [Perspective Paper](https://arxiv.org/abs/2301.04819) \\| [知乎](https://zhuanlan.zhihu.com/p/617057227) \\| [Blog](https://medium.com/towards-data-science/what-are-the-data-centric-ai-concepts-behind-gpt-models-a590071bb727) |\n| [NeuroShard: Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models](https://github.com/daochenzha/neuroshard) | [MLSys'23 Paper](https://arxiv.org/abs/2305.01868) |\n| [DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning](https://github.com/kwai/DouZero)  | [ICML'21 Paper](https://arxiv.org/abs/2106.06135) \\| [Demo](https://www.douzero.org/) \\| [知乎](https://zhuanlan.zhihu.com/p/526723604) \\| [Video](https://youtu.be/inHIi8sej7Y) \\| [Blog](https://medium.com/towards-data-science/douzero-mastering-doudizhu-with-reinforcement-learning-864363549c6a) |\n| [RLCard: A Toolkit for Reinforcement Learning in Card Games](https://github.com/datamllab/rlcard) | [IJCAI'20 Paper](https://www.ijcai.org/proceedings/2020/0764.pdf) \\| [Demo](https://www.douzero.org/) \\| [知乎](https://zhuanlan.zhihu.com/p/526723604) \\| [Video](https://youtu.be/krK2jmSdKZc) \\| [Blog](https://medium.com/towards-data-science/rlcard-building-your-own-poker-ai-in-3-steps-398aa864a0db) |\n| [RLCard-Showdown: Frontend for DouZero and RLCard](https://github.com/datamllab/rlcard-showdown) | [Demo](https://www.douzero.org/) |\n| [Awesome Game AI Resources on Multi-agent Learning](https://github.com/datamllab/awesome-game-ai)  |   |\n| [TODS: Automated Time-series Outlier Detection System](https://github.com/datamllab/tods) | [AAAI'21 Paper](https://arxiv.org/abs/2009.09822) \\| [Blog](https://medium.com/towards-data-science/tods-detecting-outliers-from-time-series-data-2d4bd2e91381) \\| [Video](https://youtu.be/H0bBXuDUe7s) |\n| [AutoVideo: An Automated Video Action Recognition System](https://github.com/datamllab/autovideo)  | [IJCAI'22 Paper](https://arxiv.org/abs/2108.04212) \\| [Blog](https://towardsdatascience.com/autovideo-an-automated-video-action-recognition-system-43198beff99d) \\| [Video](https://youtu.be/BEInjBjeIuo) |\n| [BED: A Real-Time Object Detection System for Edge Devices](https://github.com/datamllab/BED_main) | [CIKM'22 Best Demo Paper](https://arxiv.org/abs/2202.07503) \\| [Video](https://youtu.be/0tY31_cECCA) |\n| [PyODDS: An End-to-end Outlier Detection System](https://github.com/datamllab/pyodds) | [WWW'20 Paper](https://arxiv.org/abs/2003.05602) |\n| [DreamShard: Generalizable Embedding Table Placement for Recommender Systems](https://github.com/daochenzha/dreamshard) | [NeurIPS'22 Paper](https://arxiv.org/abs/2210.02023) |\n| [AutoShard: Automated Embedding Table Sharding for Recommender Systems](https://github.com/daochenzha/autoshard) | [KDD'22 Paper](https://arxiv.org/abs/2208.06399) |\n| [Towards Automated Over-Sampling for Imbalanced Classification](https://github.com/daochenzha/autosmote) | [CIKM'22 Paper](https://arxiv.org/abs/2208.12433) |\n| [Towards Similarity-Aware Time-Series Classification](https://github.com/daochenzha/SimTSC) | [SDM'22 Paper](https://arxiv.org/abs/2201.01413) |\n| [Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments](https://github.com/daochenzha/rapid) | [ICLR'21 Paper](https://arxiv.org/abs/2101.08152) |\n| [Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning](https://github.com/daochenzha/Meta-AAD) | [ICDM'20 Paper](https://arxiv.org/abs/2009.07415) |\n\n\n\n\n\u003c!--\n**daochenzha/daochenzha** is a ✨ _special_ ✨ repository because its `README.md` (this file) appears on your GitHub profile.\n\nHere are some ideas to get you started:\n\n- 🔭 I’m currently working on ...\n- 🌱 I’m currently learning ...\n- 👯 I’m looking to collaborate on ...\n- 🤔 I’m looking for help with ...\n- 💬 Ask me about ...\n- 📫 How to reach me: ...\n- 😄 Pronouns: ...\n- ⚡ Fun fact: ...\n--\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaochenzha%2Fdaochenzha","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdaochenzha%2Fdaochenzha","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaochenzha%2Fdaochenzha/lists"}