Zhining Liu
Applied Scientist Intern at Amazon
Urbana, Illinois, United States
Summary
🤩
Rockstar🎓
Top SchoolZhining Liu is a Ph.D. candidate in Computer Science at UIUC with seven years of research and industry experience applying machine learning to search, recommendation, and LLM grounding. They have interned at Amazon across multiple teams—Search Experience Science and Rufus—where they shipped a multi-task ranking system and a lightweight contextual highlighting method that improved LLM factuality, the latter published at ACL 2025. Earlier research experience at Microsoft focused on imbalance learning for intelligent logistics, demonstrating a strong foundation in applied ML and productionization. Comfortable bridging lab and product, Zhining combines rigorous academic training from Jilin University and UIUC with a track record of turning research ideas into deployed systems.
7 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Illinois Urbana-ChampaignMaster of Engineering - MEng, Computer Science @School of AI, Master of Engineering - MEng, Computer Science @School of AI at Jilin University
English, Chinese
Github Skills (45)
pytorch10
classification10
data-mining10
machine-learning10
machine-learning-algorithms10
ensemble-learning10
sklearn10
imbalanced-data10
deep-learning10
fairness-ml10
extensible10
nlp10
resampler10
pypi10
data-science9
Programming languages (3)
Github contributions (5)
ZhiningLiu1998/mesa
Oct 2020 - Dec 2021
NeurIPS’20 | Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题
Contributions:12 commits, 2 PRs, 11 pushes in 1 year 2 months
meta-learningensemble-modelmetaensembleimbalanced-learn
ZhiningLiu1998/ZhiningLiu1998.github.io
Sep 2019 - Feb 2023
Personal Homepage
Contributions:72 commits, 3 PRs, 120 pushes in 3 years 5 months
csspersonal-homepage
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