Greetings! I'm Zhi-ning LIU (刘芷宁).

GitHub Zhihu Steam PhD

你好! / Hello! / 안녕하세요! / こんにちは! / Здравствуй! / Bonjour! / Guten Tag! / Hola! / Ciao! / السلام عليكم!

I’m a Ph.D. student in Department of Computer Science, University of Illinois at Urbana-Champaign, working with the very nice Prof. Hanghang Tong. Before joining UIUC, I received my B.S. and M.Eng. in Computer Science from Jilin University in 2019 and 2022, respectively. During my time at Jilin U, I was fortunate to have Prof. Yi Chang as my advisor, and had the pleasure of working with Dr. Jiang Bian, Dr. Wei Cao, Dr. Pengfei Wei, and Prof. Jing Jiang.

My goal is to build practical machine learning systems that promote fairness and equity. I am particularly interested in developing algorithms and open-source softwares for unbiased, efficient, and robust learning from skewed data in real-world applications. My recent interest lies in topics related to graph data mining, especially, learning from real-world graphs with skewed data distribution.

Contact me via:
Mail: zhining.liu[AT]outlook.com or liu326[AT]illinois.edu

What's new:

[05/2023] One paper on treatment outcome forecasting accepted by KDD'23, see you in Long Beach : )
[05/2023] I'll be at Amazon@Seattle as an Applied Scientist Intern this summer!
[02/2023] Just released a major version of imbalanced-ensemble. [Docs/PyPI]
[02/2023] One paper on unsupervised anomaly detection accepted by ICDE'23, congrats to Hangting! [Code][PDF]
[03/2022] I will join Prof. Hanghang Tong's group at UIUC this fall as a Ph.D. student!
[01/2022] A curated list across all Machine Learning topics: Awesome2ML [ENG/中文]
[11/2021] What are inter-&intra-class imbalance and how do they affect learning? [PDF]
[11/2021] Check out our paper describing the IMBENS package. [PDF]
[06/2021] The imbalanced-ensemble Python package is released, try it out! [Docs/PyPI]
[10/2020] Our work on meta imbalanced learning was accepted by NeurIPS 2020. [PDF]
[06/2020] I am helping to organize ACM SIGIR 2020. Welcome!
[04/2020] We started the Awesome-Imbalanced-Learning project. Contributions are welcomed!
[10/2019] Our work on imbalanced classification was accepted by IEEE ICDE 2020. [PDF]
[07/2019] I received my B.Sc. degree from the Tang Aoqing Honors Program in Science.
[09/2018] I will intern at MSRA in the following year, supervised by Dr. Jiang BIAN and Dr. Wei CAO.

Selected Research Items :-)

"IMBENS: Ensemble Class-imbalanced Learning in Python"
Zhining Liu, et al. Preprint.
[PDF] [arXiv] [Zhihu/知乎] [Github] [Documentation] [Example Gallery] [PyPI]
"MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler"
Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, and Yi Chang*,
In 34th Conference on Neural Information Processing Systems (NeurIPS), 2020.
[PDF] [arXiv] [Video] [Zhihu/知乎] [Github]
"Self-paced Ensemble for Highly Imbalanced Massive Data Classification"
Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu.
In 36th IEEE International Conference on Data Engineering (ICDE), 2020.
[PDF] [arXiv] [Video(bilibili)] [Slides] [Zhihu/知乎] [Github] [PyPI]

Open-source Projects


GitHub stars GitHub forks
IMBENS: class-imbalanced ensemble learning in Python [Python Library]
[PDF] [Documentation] [Gallery] [PyPI] [Changelog] [Zhihu/知乎]

GitHub stars GitHub forks
Imbalanced Learning: paper, code, frameworks, and libraries [Awesome]
[English] [Chinese/中文] [Zhihu/知乎]

GitHub stars GitHub forks
Awesome2ML: a curated list across all machine learning topics [Awesome]
[English] [Chinese/中文] [Zhihu/知乎]

GitHub stars GitHub forks
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler [NeurIPS'20]
[PDF] [arXiv] [Video] [Zhihu/知乎]

GitHub stars GitHub forks
Self-paced Ensemble for Highly Imbalanced Massive Data Classification [ICDE'20]
[PDF] [arXiv] [Video] [Slides] [Zhihu/知乎]

Github Stats

Fun Facts

In the Chinese context, my name is kind of feminine, and many people think that I am a girl before they meet me.
I’m a gamer that enjoys driving and sightseeing in virtual worlds, though I don’t have a driver’s license in the real world.
I’m good at skating, but I can’t ski.


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