Jing Zhang
Finance Intern at SenseTime 商汤科技
Hong Kong, China
Summary
🤩
Rockstar🎓
Top SchoolJing Zhang is a CUHK integrated business administration student with six years of experience blending finance, marketing, and hands-on data work. Currently a finance intern at SenseTime, she pairs strong database organization and communication skills with a curiosity for data analysis and quantitative marketing. Her GitHub contributions to high-profile OpenMMLab projects (mmcv, mmdetection, mmdetection3d, mmfewshot) reveal backend and ML engineering chops—bug fixes, dataset refactors, and testing infrastructure improvements—that go beyond a typical business student profile. She has practical internship experience across finance and insurance firms and a short marketing stint, demonstrating versatility in both analytical and client-facing roles. Ambitious and technically curious, she aims to become a quantitative marketing specialist who can bridge rigorous ML tooling knowledge with business strategy.
6 years of coding experience
The Chinese University of Hong Kong (CUHK)
English, Chinese
Github Skills (17)
pytorch10
python10
data-set10
machine-learning10
3d-object-detection10
datasets10
few-shot-learning10
data-processing10
object-detection10
computer-vision10
transformer10
retinanet9
data-structures8
documentation8
data-structure8
Programming languages (3)
Github contributions (5)
open-mmlab/mmdetection
Jun 2020 - Jan 2023
OpenMMLab Detection Toolbox and Benchmark
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:605 reviews, 58 commits, 89 PRs in 2 years 7 months
Contributions summary:Jing contributed to the object detection framework by fixing bugs related to the RPN and FreeAnchorRetinaHead, including addressing issues related to softmax calculations and handling scenarios with no ground truth. Further contributions include implementing the PAA assignment algorithm, adding new configurations, and making improvements to its functionalities. The user also worked on reimplementing the Sparse R-CNN model, suggesting proficiency in developing and integrating different object detection models.
retinanetbenchmarkfast-rcnnopenmmlabsemisupervised-learning
open-mmlab/mmdetection3d
Apr 2022 - Oct 2022
OpenMMLab's next-generation platform for general 3D object detection.
Role in this project:Backend Developer
Backend DeveloperContributions:42 reviews, 25 commits, 17 PRs in 6 months
Contributions summary:Jing contributed to the documentation, specifically updating the documentation parsing process with Myst-parser. They addressed bugs in the core functionality, including fixes for `NaiveSyncBatchNorm1d` and `NaiveSyncBatchNorm2d`. The user also refactored dataset loading and preprocessing pipelines, modifying the KITTI dataset and refactoring the ScanNet and SUNRGBD datasets, while also refactoring transforms. Additionally, they made several refactors to core classes and interfaces.
pytorchnext-generationkitti-datasetdeep-learningobject-detection
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