Wei Dai

MSCS student at Stanford University

About me

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