Welcome!

I am a first year Ph.D. student majoring in Computer Science at Vanderbilt University advised by Dr. Tyler Derr.

My research interest lies in the domains of applied-machine learning and data mining on graphs with an emphasis on deep learning on graphs. More specifically, I am currently researching graph neural networks (GNNs) focusing on ways to leverage high-order attention and neighorhood information to tackle the over-smoothing and over-squashing problem in deep graph neural network models, which imposes significant impact on learning better representations for tasks such as node classification, link prediction and community detection. Meanwhile, I am highly interested in applying various self-supervised learning strategies including contrastive learning to further boost the performance of GNNs..

News

9/2021
Preprint of our review ‘Graph Neural Networks: Self-supervised Learning’
8/2021
Invited to serve as PC member for AAAI2021!
8/2021
Serving as the session chair at KDD2021!
7/2021
Our paper 'Tree Decomposed Graph Neural Network' is accepted to ACM CIKM'21!
3/2021
Awarded Student Travel Award to attend SDM'21 supported by NSF!
3/2021
Poster presentation at SDM'21 Doctoral Forum!
1/2021
Awarded free registration and volunteer position at IJCAI'20!
1/2021
Excited to join VU-NDS lab with superivsion under Dr. Derr!

2020

11/20
Our paper ‘‘A Data-Integration Analysis on Road Emissions and Traffic Patterns’’ is accepted at Smoky Mountains Computational Sciences and Engineering Conference 2020. Springer, Cham!
8/20
Best Paper Award in SMC Data Challenge 2020!

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