Xin Fu is a Software Engineer with a decade of experience building scalable AI/ML platforms and runtimes, currently advancing generative AI infrastructure at Bloomberg in London. He has deep hands-on experience deploying serverless inference on Kubernetes (Knative, KServe) and has built production ML pipelines at companies including Uber, Microsoft Research, Xiaomi, and UBC. A practical full-stack contributor, Xin blends model work (GANs, CapsNet, VAEs) with engineering—containerized deployments, TensorRT optimizations, and TensorFlow 2 migrations—to close the gap between research and reliable production. He is active in open source, contributing front-end VuePress templates and LaTeX thesis tooling, showing a taste for polished developer UX and reproducible documentation beyond core ML. Academically grounded with an MEng from Cornell and a strong undergraduate record from Wuhan University, he pairs rigorous research experience with pragmatic platform engineering.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering - BE, Electronic Information Engineering, GPA 3.78, Bachelor of Engineering - BE, Electronic Information Engineering, GPA 3.78 at Wuhan University
Master of Engineering - MEng, Electrical and Computer Engineering, GPA 3.88, Master of Engineering - MEng, Electrical and Computer Engineering, GPA 3.88 at Cornell University
:page_facing_up: Elegant & friendly homepage (bio, tech portfolio, resume, doc...) template with Markdown and VuePress
Role in this project:
Front-end Developer
Contributions:48 commits, 22 PRs, 28 pushes in 1 year 9 months
Contributions summary:Xin primarily focused on developing the front-end components and layout of the VuePress-based homepage. Their contributions include adding and modifying Vue.js components such as `Homepage`, `Projects`, and `MContent`, and introducing new components like `AboutCard` and `ProfileSection`. They also updated the configuration file and stylesheet to customize the appearance and functionality of the website, including supporting features like emoji and Katex.
:smiley_cat: Pretty & simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes.
Role in this project:
Full-stack Developer
Contributions:35 commits, 28 PRs, 33 pushes in 3 years 11 months
Contributions summary:Xin significantly updated the image classification web application's interface and functionality. They refactored the frontend by removing Bootstrap and third-party JavaScript libraries, implementing drag-and-drop image uploading, and adding a result display box. They upgraded the backend by migrating to TensorFlow 2.0 and modifying the API to return results in JSON format. The user also implemented utility functions and updated the styles for a better user experience.
pythonclassifierflaskapp-templatetensorflow
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.