I am a fourth-year Ph.D. candidate at Washington University in St. Louis. I focus on studying and improving Graph Neural Networks (GNNs). My current target is to reduce the complexity of powerful GNNs. I am also interested in general ML and its clinical application. Recently, ICD auto-coding and multi-modal study using ICD code draw my attention.

Very recent interests on developing universal graph foundation model! Our preliminary work is here. I am excited to talk about related ideas.

I obtained my Bachelor’s degree also from Washington University in St. Louis. It is my honor to be advised by Dr. Yixin Chen towards my Ph.D. degree. For details, check out my CV.

I am actively looking for internship Summer 2024. If you are interested in my work, I would love to chat and discuss potential opportunities.

🔥 News

• 2024.01:  🎉🎉 COLA accpeted by WWW2024! Congratulations to Hao!
• 2024.01:  🎉🎉 OneForAll paper accepted as Spotlight (5%) by ICLR2024. Thanks everyone for the great teamwork!
• 2023.09: Check out our newest work combining Graph Neural Networks with LLMs! (Code, Paper) Using LLM, we design a GNN that is cross-domain (citation network, molecular graph, etc) and cross-task (node-level, link-level, zero-shot, etc), potentially serving as a pathway to graph foundation model.
• 2023.09:  🎉🎉 Two paper, MAG-GNN and (k,t)-FWL accepted by Neurips 23!
• 2022.09:  🎉🎉 Our paper Geodesic Graph Neural Network for Efficient Graph Representation Learning accepted by Neurips 22!

📝 Publications

• NeurIPS 2023 MAG-GNN: Reinforcement Learning Boosted Graph Neural Network, Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang
• NeurIPS 2023 Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman, Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen
• NeurIPS 2022 Geodesic Graph Neural Network for Efficient Graph Representation Learning, Lecheng Kong, Yixin Chen, Muhan Zhang
• IJCAI 2022 Manipulating Elections by Changing Voter Perceptions, Junlin Wu, Andrew Estornell, Lecheng Kong, Yevgeniy Vorobeychik
• Preprint One for All: Towards Training One Graph Model for All Classification Tasks, *Hao Liu, *Jiarui Feng, *Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang
• Preprint A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks, Lecheng Kong, Christopher King, Bradley Fritz, Yixin Chen
• Preprint Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks, Hao Liu, Jiarui Feng, Lecheng Kong, Dacheng Tao, Yixin Chen, Muhan Zhang
• Preprint Time Associated Meta Learning for Clinical Prediction, Hao Liu, Muhan Zhang, Zehao Dong, Lecheng Kong, Yixin Chen, Bradley Fritz, Dacheng Tao, Christopher King

(* Equal Contribution)

🎖 Honors and Awards

• 2022/2023 NeurIPS travel award.
• 2007.08 Chunjianghuayue Young Residents Swimming Competition, Runner-up.

🤝 Services

• Reviewer for conferences: CVPR23/24; NeurIPS23; ICLR24;

📖 Educations

• 2020.09 - (now), Ph.D., Computer Science, Washington University in St. Louis.
• 2016.09 - 2020.06, Bachelor’s/Master’s, Computer Science, Washington University in St. Louis.
• 2010.9 - 2016.06, High School, Academic, Hangzhou Foreign Language School.

💻 Internships

• 2019.05 - 2019.08, Google, Mountain View.

Personal

• I am from Hangzhou, China.
• I enjoy badminton🏸 and skiing⛷️.
• Game enthusiast with horrible gaming skills.