I am a masters student at Stanford University majoring in Computer Science. I am currently in Stanford SVL and Partnership in AI-Assisted Care (PAC) Lab supervised by Dr. Li Fei-Fei and Dr. Ehsan Adeli.
Before joining Stanford, I graduated with the highest honor in Computer Science and Math from Emory University. I was in Emory Brain Network Lab under the supervision of Dr. Carl Yang, working on graph mining in the area of healthcare.
Before joining Emory Brain Network Lab, I worked with Dr. John Duncan on umbral moonshine and others. My work was primarily on determining the modular form trace functions obtained from the action of Spin(24) on V-supernatural.
My research interests lie in graph data mining, with an emphasis on interpretable machine learning, graph neural networks and multi-modality learning.
Wei Dai, Hejie Cui, Xuan Kan, Ying Guo, Carl Yang: Transformer Based Hierarchical Clus- tering On Brain Networks, IEEE International Symposium on Biomedical Imaging (IEEE-ISBI), 2023.
Xuan Kan, Wei Dai, Hejie Cui, Zilong Zhang, Ying Guo, Carl Yang: Brain Network Transformer, Conference on Neural Information Processing Systems (NeurIPS), 2022. (Oral Presentation)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang. Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis, MICCAI, 2022. (Oral Presentation, Poster)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang. BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks, IEEE-TMI, 2022.
Wei Dai: Introduction to Monstrous Moonshine, Emory Undergraduate Research Symposia (EURS), 2021
Megan Lagerquist, Wei Dai, Teresa Yu, Yi Cao: Cross-Culture Analysis of Gender and Royalty in Folktales with an Application of Natural Language Processing Tools, SouthEastern Undergraduate Sociology Symposium (SEUSS), 2021