Zhun Zhong
Assistant Professor at University of Nottingham
Nottingham, England, United Kingdom
Summary
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Senior🎓
Top SchoolZhun Zhong is an Assistant Professor at the University of Nottingham with a decade of experience at the intersection of computer vision and trustworthy AI, focused on robust visual recognition. He progressed from postdoctoral research to faculty roles in Italy and the UK after earning a PhD from Xiamen University with a joint stint at the University of Technology Sydney. His research and engineering work emphasize practical robustness techniques—evidenced by contributions to the widely used Random Erasing data augmentation for image classification and PyTorch compatibility updates. Zhun combines academic rigor with hands-on ML engineering, maintaining and improving reproducible codebases that bridge research and deployment. Colleagues value his ability to translate theoretical insights into well-documented experiments and usable tools for the vision community.
10 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Xiamen UniversityJoint PhD Student, Computer Science, Joint PhD Student, Computer Science at University of Technology Sydney
Github Skills (6)
pytorch10
computer-vision10
data-augmentation10
image-classification10
python9
object-detection6
Programming languages (4)
Github contributions (5)
zhunzhong07/Random-Erasing
Sep 2017 - Jun 2021
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
Role in this project:
ML Engineer
ML EngineerContributions:56 commits, 1 PR, 51 pushes in 3 years 9 months
Contributions summary:Zhun contributed significantly to the project by implementing and modifying core components related to image classification and data augmentation techniques. The commits show the addition of new files and modifications to existing ones, suggesting the user's focus on integrating random erasing data augmentation, including parameter configurations for this technique. Further contributions included the update of the cifar.py and fashionmnist.py scripts for PyTorch 1.0 compatibility, indicating an active role in maintaining and improving the model's functionality and adapting it to updated frameworks.
imagenetefficientnetdeep-learningcifar10backbone
zhunzhong07/person-re-ranking
Mar 2017 - Oct 2021
Contributions:80 commits, 50 pushes, 1 branch in 4 years 8 months
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