Jianwei Yang

Washington, United States

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Summary

🤩

Rockstar

Jianwei Yang is a research-driven Member of Technical Staff with 12 years of experience building state-of-the-art multimodal and vision AI systems across industry leaders including Microsoft, Meta, and xAI. He has led development of influential models and architectures—such as Focal Transformer, UniCL, X-Decoder, and Phi-3-V variants—that advanced image/video understanding, grounding, and agentic capabilities for UI navigation and robotics. A prolific ML engineer and open-source contributor, his PyTorch implementations for scene graph generation and Faster R-CNN remain widely used by the community. Jianwei combines deep academic training (PhD-level work across Georgia Tech, Virginia Tech, and CAS) with product-focused research, and is known for inventing practical prompting and parsing techniques (Set-of-Mark, OmniParser) that accelerated multimodal agent development.

12 years of coding experience

Github Skills (12)

model-building10

gpu-programming10

computer-vision10

pytorch10

machine-learning10

faster-rcnn10

deep-learning10

modeling10

model-driven10

model-driven-development10

back-end-development8

python8

Programming languages (8)

C++JavaScriptLuaHTMLJupyter NotebookMATLABPythonCuda

Github contributions (5)

jwyang/faster-rcnn.pytorch

Aug 2017 - May 2020

A faster pytorch implementation of faster r-cnn

Role in this project:

Back-end Developer

Contributions:312 commits, 49 PRs, 255 pushes in 2 years 10 months

Contributions summary:Jianwei primarily focused on integrating and adapting a PyTorch implementation of Faster R-CNN for GPU processing. Their work involved adding a PyTorch-based non-maximum suppression (NMS) library and modifying the NMS wrapper to support the GPU version. They adapted various RPN and ROI layers to utilize the GPU-accelerated NMS. Additional contributions involved incorporating image trimming and mini-batch loading to the project.

faster-rcnnpytorch

jwyang/graph-rcnn.pytorch

Jul 2018 - Mar 2020

[ECCV 2018] Official code for "Graph R-CNN for Scene Graph Generation"

Role in this project:

Back-end Developer & ML Engineer

Contributions:198 commits, 7 PRs, 180 pushes in 1 year 9 months

Contributions summary:Jianwei primarily contributed to the implementation of a scene graph generation model, which involved the creation of a baseline model. The code changes included adding the necessary model, loss function, and data loading components for the project. They worked on defining the model architecture and setting up the training process for the scene graph generation task, utilizing PyTorch for machine learning implementation.

graphscene-graph

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