Yunfan Shi
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolYunfan Shi is a machine learning engineer with five years’ experience building and deploying computer vision and ML systems across academia and industry. He has contributed to the unified ML framework Ivy—implementing TensorFlow and PyTorch activation functions and frontends—and has hands-on experience deploying Llama 2/GPT-4 based web apps with LangChain and Gradio. His background spans autonomous driving pipelines, night-data synthesis for obstacle and lane detection, and lightweight deployment on edge devices like the Jetson Nano. Comfortable with research-to-production workflows, he has evaluated and accelerated generative and discriminative models (StyleGAN, Stable Diffusion, YOLO variants) and automated data pipelines for large-scale datasets. Based in London, he combines rigorous academic training (UCL, University of Liverpool, XJTLU) with practical engineering instincts, often spotting code-organization issues and suggesting product-level improvements. A pragmatic problem-solver, he bridges privacy-preserving web development and scalable ML engineering in real-world environments.
5 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of LiverpoolBachelor of Science - BS, Information and Computing Science, Bachelor of Science - BS, Information and Computing Science at Xi'an Jiaotong-Liverpool UniversityUniversity College London
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
pytorch10
tensorflow10
python10
converter9
machine-learning9
deep-learning8
neural-network8
testing8
numpy7
Programming languages (1)
Github contributions (5)
ivy-llc/ivy
Jul 2022 - Dec 2022
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 9 commits, 11 PRs in 6 months
Contributions summary:Yunfan contributed to the project by updating and implementing functionalities for TensorFlow within the ivy library. This involved modifying activation functions, specifically the `hard_sigmoid` function, and updating corresponding tests. Additionally, the user worked on updating the `real` method in the torch frontend. These updates demonstrate a focus on supporting multiple machine learning frameworks within ivy.
pythontensorflowframework-learningtemplatedata-science
FrankShi9/ivy
Aug 2022 - Sep 2022
The Unified Machine Learning Framework
Contributions:50 commits, 53 pushes, 1 branch in 1 month
pythondata-sciencedeep-learningmachine-learningframework-learning
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