The one in pink is me :)
N410, 201 Dowman Drive
Atlanta, Georgia 30322
My name is Xuan Kan (阚璇). I obtained my bachelor’s degree in Software Engineering at Tongji University, Shanghai, advised by Prof. Lin Zhang. During my undergraduate study, my research focused on pervasive and trustworthy systems design and implementation using machine learning methods supervised by Prof. Xiaoxuan Lu at University of Oxford.
Currently, I am pursuing my Ph.D. degree in computer science at Emory University under the joint supervision of Prof. Carl Yang and Prof. Ying Guo. My research goal aims to design more efficient and interpretable machine learning algorithms for fMRI data, which can assist in neurobiological findings and mental disease diagnosis.
|Sep 21, 2023
|Our work entitled Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting accepted to NeurIPS 2023. Congrats to Hejie!
|Aug 25, 2023
|One paper entitled Dynamic Brain Transformer with Multi-level Attention for Functional Brain Network Analysis has been accepted for IEEE BHI 2023. Very appreciate the travel awrad from the conference. See you in Pittsburgh!
|Jun 10, 2023
|Ending my Google Intership and will start my next journey at Meta in Seattle, WA. See you soon, Seattle!
|May 17, 2023
|Our work entitled R-Mixup: Riemannian Mixup for Biological Networks accepted to KDD 2023. The arxiv version can be found here!
|Mar 30, 2023
|Two paper accepted to ISBI 2023. Congrats to my collaborators!
- KDDR-Mixup: Riemannian Mixup for Biological NetworksProceedings of the ACM International Conference on Knowledge Discovery and Data Mining 2023 (Co-first author)
- NeurIPSBrain Network TransformerProceedings of the Conference on Neural Information Processing Systems 2022Also Presented in Workshop ICML-IMLH 2022 (Oral, no proceedings)
- MIDLFBNetGen: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation (Oral)Medical Imaging with Deep Learning 2022Also Presented in Workshop ICML-IMLH 2021 (no proceedings)
- ECML-PKDDZero-shot Scene Graph Relation Prediction through Commonsense Knowledge IntegrationThe European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2021