I’m a third-year Ph.D. candidate in the Department of Computer Science and Engineering, Washington University in St.Louis (WashU). I’m fortunately supervised by Dr. Yixin Chen and Dr. Fuhai Li. My main research area lies in solving fundamental problems in graph representation learning and graph neural networks (GNNs). Particularly, my works focus on the following aspects:
- Understanding and improving the expressiveness of GNNs.
- Improving the structure learning ability of GNNs in an efficient way.
- Leveraging LLMs to Design foundational graph model for solving various tasks in graph domain.
- The application of GNNs in precision medicine, with a particular interest in the gene interaction network discovery.
🔥 News
- 2024.04: 🎉🎉 PathFinder is accepted by Frontiers in Cellular Neuroscience!
- 2024.01: 🎉🎉 COLA is accepted by WWW 2024! Congratulations to Hao!
- 2024.01: 🎉🎉 OFA is accepted by ICLR 2024 as a Spotlight(5%)!
- 2024.01: 🎉🎉 sc2MeNetDrug is accepted by PLOS Computational Biology!
- 2023.10: We have developed a novel R Shiny application sc2MeNetDrug for the analysis of single-cell RNA-seq data. This application enables the identification of activated pathways, up-regulated ligands and receptors, cell-cell communication networks, and potential drugs to inhibit dysfunctional networks. Moreover, it provides user-friendly UI for easy usage! Check out our GitHub repository and website for more details. This project is still ongoing, and we welcome any comments or suggestions!
- 2023.10: Leveraging the power of language and LLMs, we propose One-for-ALL (OFA), which is the first general framework that can use a single graph model to address (almost) all different graph classification tasks from different domains. Check out our preprint and code!
- 2023.09: 🎉🎉 (k,t)-FWL+, MAG-GNN, and d-DRFWL2(spotlight) are accepted by NeurIPS 2023!
- 2023.06: 🎉🎉 Passed the oral exam!
- 2022.09: 🎉🎉 Our paper “How powerful are K-hop message passing graph neural networks” is accepted by NeurIPS 2022. See you in New Orleans!
- 2022.08: 🎉🎉 Our paper “Reward delay attacks on deep reinforcement learning” is accepted by GameSec 2022.
📝 Selected Publications
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 (* Equal contribution)
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
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
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power
Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network
Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang
How powerful are K-hop message passing graph neural networks
Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang
Reward Delay Attacks on Deep Reinforcement Learning
Anindya Sarkar, Jiarui Feng, Yevgeniy Vorobeychik, Christopher Gill, Ning Zhang
You can browse my full publication list in Google Scholar
🎖 Honors and Awards
- 2023.10 NeurIPS 2023 Travel Award.
- 2021.07 ICIBM 2021 Travel Award.
📖 Educations
- 2021.09 - Present, Ph.D student, Washington University in St. Louis, MO, USA.
- 2019.09 - 2021.05, Master, Washington University in St. Louis, MO, USA.
- 2015.09 - 2019.06, Bachelor, South China Univerity of Technology, GuangZhou, China.
💻 Internships
- 2019.06 - 2019.08, Alibaba Cloud, HangZhou, China.
- 2018.12 - 2019.02, Credit card center, GuangZhou Bank, GuangZhou, China.
🔬Services
- Conference reviewer: CVPR23; NeurIPS23; ICLR24; CVPR24;
🎮 Misc
- Crazy computer gamer: Overwatch, APEX, World of warcraft, PUBG, CS:GO…
- I have a cute ragdoll called $\theta$, I love him!!!!!!!!!!!!!