Portrait of Xinyu Yuan

Xinyu Yuan

Lab Representative
PhD - Université de Montréal
Supervisor
Research Topics
Computational Biology
Deep Learning
Generative Models
Graph Neural Networks
Knowledge Graphs
Multimodal Learning

Biography

Xinyu Yuan is a second-year PhD student at Mila, advised by Prof. Jian Tang. Her research passionately delves into the realm of representation learning for biological data, to harness AI’s potential to advance understanding of biological systems and processes, with a particular emphasis on scalability and transferability. From the technique perspective, she specializes in large-scale graph representation learning for knowledge graph completion, and pre-training, transfer learning, and multi-modality learning with language models. In particular, knowledge graphs serve as an important bridge to connect all the different data modalities in biological domain. In the same time, language models serve as foundational tools for each data modality, to extract effective representations and infer latent patterns and deep structure that go well beyond the capacity of humans. She also spent some time in Intel AI Lab. And she obtained a bachelors’ degree in computer science from Peking University.