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Hello there 👋🏻, my name is Xinyan.

Packages I code with:

PyTorch TensorFlow Keras

🎓 I am a Master of Engineering student at Imperial College London (2019-2023) | Website

💻 I am a member of the Algorithmic Human Development Group at the Department of Computing, and my research experinces extended to Imperial College Data Science Institute where I have worked on projects related to biomedical data science.

💊 My research focuses on the application of machine learning to biomedicine and healthcare, including projects on biomedical image segmentation, biomedical knowledge graph construction, and sentimental analysis of patient diaries.

🦾 I worked with Machine Learning Engineers at Alipay to implement Graph Neural Networks for uses in causal inference analysis of market schemes and the building of a recommendar system. link to implementation

🧬 I am currently working on my master thesis on the application of geometric deep learning to protein design! Check out my experiments on SO(3)-Invariant Representation on ProteinMPNN. link to project

💬 Also, I am hosting a weekly paper reading group, sharing Graph Transformers on molecular representation learning with researchers from the fields of Computing, Medicine, Pharmaceutics etc. link to notebooks

🌱 I led a team of AI enthusiasts working on proposals for AI-based solutions to the Sustainable Development Goals. Our mental healthcare initiative was selected as a top 10 finalist out of 200+ teams by the UNDP judging panel.

Xinyan Ye's Projects

causal_knowledge_gnn icon causal_knowledge_gnn

This is the code implementation for the paper Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge

data_mining icon data_mining

Intern projects on Recommender System, Time Series Forecast, Sentiment Analysis

e3nn_tutorial icon e3nn_tutorial

repository and website for tutorials on 3d Euclidean equivariant neural networks

so3_invariant_proteinmpnn icon so3_invariant_proteinmpnn

This is the code for the master thesis on building rotation invariant representation for protein design pipeline

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