Haoyu Xie
Data Research Analyst
Sheffield, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolHaoyu Xie is a Data Research Analyst with eight years of cross-disciplinary experience blending data science, software engineering and research, currently based in Sheffield. He has built healthcare analytics tools—DEA/TOPSIS web applications and neural-network–based data quality systems—to evaluate and forecast provincial health resource allocation across two decades. With a PhD focus on crowdsourcing and hands-on development background in Unity C#, Python Flask, and MySQL, he bridges academic rigour and production engineering, including realtime databases and authentication for user-data collection. Haoyu also contributes to open-source ML tooling such as the FaceChain project, improving image-generation prompts and inference pipelines to refine digital-twin outputs. Colleagues value his ability to translate complex evaluation methodologies into usable systems and uncover non-obvious correlations between inputs and outputs in large, noisy healthcare datasets.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Applied Science (B.A.Sc.), Management Information Systems, General, Bachelor of Applied Science (B.A.Sc.), Management Information Systems, General at Iowa State UniversityHeriot-Watt University Edinburgh CampusDoctor of Philosophy - PhD, Groupwork in Crowdsourcing, Doctor of Philosophy - PhD, Groupwork in Crowdsourcing at The University of Sheffield
English, Chinese
Github Skills (7)
prompt-engineering10
computer-vision10
machine-learning10
stable-diffusion10
image-generation10
python10
pytorch9
Programming languages (2)
Github contributions (5)
modelscope/facechain
Aug 2023 - Feb 2024
FaceChain is a deep-learning toolchain for generating your Digital-Twin.
Role in this project:
ML Engineer
ML EngineerContributions:11 PRs, 1 branch, 1 comment in 5 months
Contributions summary:Haoyu primarily contributed to the `facechain` repository by modifying and updating the `constants.py` and `inference.py` files. The changes include the addition and modification of styles and prompts for image generation and modifications to the inference pipeline. These updates suggest an involvement in refining the image generation process and incorporating new aesthetic options, indicating a focus on model configuration and usage.
Haoyu-Xie/PRCL
Mar 2022 - Nov 2022
Contributions:84 commits, 16 pushes, 1 comment in 8 months
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