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Howdy! I am a third-year PhD student from the Department of Computer Science and Engineering at Texas A&M University, working with Dr. Xia (Ben) Hu. I received my Bachelor degree in Computer Science from Wuhan University in 2018, working with Dr. Chenliang Li. I was a Research Intern at Seattle AI Lab of Kuai Inc. in Summer 2020, working with Dr. Wenye Ma and Dr. Ji Liu.

My research mainly focuses on machine learning and data mining. In particular, I am interested in Reinforcement Learning (RL) and Automated Machine Learning (AutoML). I am also interested in their applications in Anomaly and Outlier Detection, Graph Neural Networks, Time-Series Analysis, Recommender Systems, and Machine Learning Systems, etc.

Open-Source Projects

RLCard: A Toolkit for Reinforcement Learning in Card Games (>900 stars)

Presented in IJCAI 2020
[Website] | [Paper] | [Code] | [Video]

TODS: An Automated Time-series Outlier Detection System (>200 stars)

Presented in AAAI 2021
[Website] | [Paper] | [Code] | [Video]

PyODDS: An End-to-end Outlier Detection System (>100 stars)

Presented in WWW 2020
[Website] | [Paper] | [Code]

Publications

[Google Schorlar]
* Equal contribution

2021

Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments

Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu
ICLR 2021, International Conference on Learning Representations
[PDF] | [Code]

AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning

Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, and Xia Hu
ICDE 2021, IEEE International Conference on Data Engineering

TODS: An Automated Time Series Outlier Detection System

Kwei-Herng Lai*, Daochen Zha*, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Minyang Wan, Diego Martinez, Xia Hu
AAAI 2021, AAAI Conference on Artificial Intelligence, demo track

2020

Towards Deeper Graph Neural Networks with Differentiable Group Normalization

Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, and Xia Hu
NeurIPS 2020, Neural Information Processing Systems
[PDF] | [Code]

Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning

Daochen Zha, Kwei-Herng Lai, Mingyang Wan, and Xia Hu
ICDM 2020, IEEE International Conference on Data Mining
[PDF] | [Slide] | [Code]

PolicyGNN: Aggregation Optimization for Graph Neural Networks

Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, and Xia Hu
KDD 2020, ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[PDF]

RLCard: A Platform for Reinforcement Learning in Card Games

Daochen Zha*, Kwei-Herng Lai*, Songyi Huang∗, Yuanpu Cao, Keerthana Reddy, Juan Vargas, Alex Nguyen, Ruzhe Wei, Junyu Guo, and Xia Hu
IJCAI 2020, International Joint Conference on Artificial Intelligence, demo track
[PDF] | [Code] | [Video]

Dual Policy Distillation

Daochen Zha*, Kwei-Herng Lai* Yuening Li, and Xia Hu
IJCAI 2020, International Joint Conference on Artificial Intelligence
[PDF] | [Code]

Multi-Channel Graph Neural Networks

Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, and Xia Hu
IJCAI 2020, International Joint Conference on Artificial Intelligence
[PDF]

PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning

Yuening Li, Daochen Zha, Praveen Venugopal, Na Zou, and Xia Hu
WWW 2020 Web Conference, demo track
[PDF] | [Code]

RLCard: A Toolkit for Reinforcement Learning in Card Games

Daochen Zha, Kwei-Herng Lai, Yuanpu Cao, Songyi Huang, Ruzhe Wei, Junyu Guo, and Xia Hu
AAAI-Workshop 2020, AAAI-20 Workshop on Reinforcement Learning in Games
[PDF] | [Code] | [Video]

2019

Multi-Label Dataless Text Classification with Topic Modeling

Daochen Zha, and Chenliang Li
KAIS 2019, Knowledge and Information Systems Journal
[PDF] | [Code]

Experience Replay Optimization

Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, and Xia Hu
IJCAI 2019, International Joint Conferences on Artificial Intelligence
[PDF] | [Slide]