Zhining Liu

Zhining Liu

Everything should be made as simple as possible, but not any simpler.

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. candidate at Department of Computer Science, University of Illinois at Urbana-Champaign, working with the very nice Prof. Hanghang Tong. Before joining UIUC, I received both my B.S. and M.Eng. in Computer Science from Jilin University in 2019 and 2022, where I was fortunate to have Prof. Yi Chang as my advisor. I was also a research intern at MLGroup@Microsoft Research Asia in 2018 and an Applied Scientist Intern at SearchScience@Amazon in 2023 and 2024.

I enjoy doing research and developing open-source softwares for unbiased, efficient, and robust machine learning from skewed data in real-world applications. My recent interest lies in graph data mining (ICML’24), class-imbalanced learning (ICML’24,NeurIPS’20,ICDE’20), and fairness-aware machine learning (KDD’24, FAccT’24).

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

🌈 What's new:

  • [05/2024] 🍻KDD'24: "AIM: Attributing, Interpreting, Mitigating Data-encoded Unfairness". [Code/PDF]
  • [05/2024] 🧑‍💻Intern@Amazon: Starting my Applied Scientist Internship at BayArea!
  • [04/2024] 🍻ICML'24: "Class-Imbalanced Graph Learning without Class Rebalancing". [Code/PDF]
  • [03/2024] 🍻FAccT'24: "Group Fairness via Group Consensus" (with Eunice Chan). [PDF]
  • [05/2023] 🍻KDD'23: "Web-based Long-term Spine Treatment Outcome Forecasting" (with Hangting Ye). [PDF]
  • [05/2023] 🧑‍💻Intern@Amazon: Starting my Applied Scientist Internship at Seattle!
  • [02/2023] 💾Open-source: Major release of IMBENS - imbalanced learning toolbox [Github/Docs/PyPI]
  • [02/2023] 🍻ICDE'23: "UADB: Unsupervised Anomaly Detection Booster" (with Hangting Ye). [Code/PDF]
  • [03/2022] 🎓Starting Ph.D.@UIUC: I will join Prof. Hanghang Tong's group at UIUC in 2022 Fall!
  • [01/2022] 💾Open-source: Awesome2ML - a curated list across all Machine Learning topics. [ENG/中文]
  • [11/2021] 📜Preprint: "IMBENS: Ensemble Class-imbalanced Learning in Python" [Code/PDF]
  • [06/2021] 💾Open-source: IMBENS - imbalanced learning toolbox [Github/Docs/PyPI]
  • [10/2020] 🍻NeurIPS'20: "MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler" [Code/PDF]
  • [04/2020] 💾Open-source: Awesome-Imbalanced-Learning - a curated list of imbalanced learning resources.
  • [10/2019] 🍻ICDE'20: "Self-paced Ensemble for Highly Imbalanced Massive Data Classification" [Code/PDF]
  • [07/2019] 🎓Graduation@JilinU: Recieved my B.Sc. from Tang Aoqing Honors Program in Science, Jilin University.
  • [09/2018] 🧑‍💻Intern@Microsoft: Starting my internship at Microsoft Research Asia! Supervisor: Dr. Jiang BIAN, Dr. Wei CAO.

🎓 Featured Research Items (GoogleScholar)

"Class-Imbalanced Graph Learning without Class Rebalancing"
Zhining Liu, et al. In ICML'24.
[PDF] [arXiv] [Zhihu/知乎] [Github]
"IMBENS: Ensemble Class-imbalanced Learning in Python"
Zhining Liu, et al. Open-source Python Package.
[PDF] [arXiv] [Zhihu/知乎] [Github] [Documentation] [Example Gallery] [PyPI]
"MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler"
Zhining Liu, et al. In NeurIPS'20.
[PDF] [arXiv] [Video] [Zhihu/知乎] [Github]
"Self-paced Ensemble for Highly Imbalanced Massive Data Classification"
Zhining Liu, et al. In IEEE ICDE'20.
[PDF] [arXiv] [Video(bilibili)] [Slides] [Zhihu/知乎] [Github] [PyPI]

💾 Featured Open-source Projects (Github)


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]

📈 My Github Stats

🕺 Fun Facts

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