Jihan Yang
Founding Scientist at AMI - Advanced Machine Intelligence
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolJihan Yang is a founding scientist and machine learning researcher with nine years of experience bridging academic rigor and production ML for computer vision and 3D perception. After earning a PhD in Machine Learning and Computer Vision from The University of Hong Kong, she completed a postdoc and research internships at NYU Courant, SenseTime, Tencent, and YITU, working closely with leaders like Prof. Saining Xie. Her open-source contributions to OpenPCDet demonstrate hands-on expertise improving loss functions and dataset pipelines for LiDAR-based 3D object detection, including integrations for Waymo and Lyft benchmarks. Now based in New York, she combines deep research experience with startup execution as a founder, routinely translating state-of-the-art methods into deployable training and evaluation workflows. Colleagues note her uncommon blend of rigorous theory understanding and pragmatic engineering that accelerates model development from paper to practice.
9 years of coding experience
Bachelor of Engineering - BE, Software Engineering, Bachelor of Engineering - BE, Software Engineering at Sun Yat-sen UniversityThe University of Hong Kong (HKU)
Github Skills (5)
object-detection10
pytorch10
machine-learning10
point-cloud10
tensor9
Programming languages (3)
Github contributions (5)
open-mmlab/OpenPCDet
Jun 2020 - Nov 2022
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 33 commits, 58 PRs in 2 years 5 months
Contributions summary:Jihan implemented training losses and modifications to loss functions, including SigmoidFocalClassificationLoss and WeightedSmoothL1Loss, within the `pcdet/utils/loss_utils.py` file. They also worked on integrating the SECOND-IoU method and baseline results. Furthermore, they contributed to dataset processing, including adjustments related to the Waymo dataset and Lyft dataset. These contributions suggest a focus on improving the model training and evaluation pipelines for object detection in point cloud data.
pytorchtoolboxobject-detectionpv-rcnncomputer-vision
jihanyang/OpenPCDet
May 2022 - Feb 2023
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
Contributions:11 commits, 5 PRs, 36 pushes in 8 months
toolboxobject-detectioncomputer-vision3d-object-detectionopenpcdet
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