I’m currently a Research Scientist at Meta MRS. Prior to that, I received my Ph.D. from the Department of Computer Science and Engineering, Washington University in St. Louis (WashU), where I was fortunately supervised by Dr. Yixin Chen and also worked closely with Dr. Fuhai Li.
My research spans Graph Neural Networks (GNNs), Large Language Models (LLMs), and Generative Recommendation. Specifically, I work on:
- Expressiveness of GNNs — characterizing and improving the structure-learning capacity of message-passing architectures.
- LLMs and graphs — understanding the capabilities and limitations of LLMs on graph tasks, integrating GNNs with LLMs toward graph foundation models, and developing test-time training methods that adapt LLMs to graph reasoning.
- Scaling Mixture-of-Experts (MoE) — improving the quality and efficiency of sparsely activated models at scale.
- Diffusion models for sequential data — analyzing discrete and continuous diffusion models on language and recommendation data, and building large-scale generative recommenders based on masked diffusion.
🔥 News
- 2026.09: 🎉🎉 TabDLM is accepted by NeurIPS 2026! Congratulations to Donghong!
- 2026.08: 🎉🎉 ReMix is accepted by COLM 2026! Congratulations to Ruizhong!
- 2026.05: 🎉🎉 GRIP is accepted by KDD 2026, research track!
- 2026.04: 🎉🎉 DAG-MoE is accepted by ICML 2026!
- 2026.04: 🎉🎉 Joined Meta MRS as a Research Scientist!
- 2026.02: 🎉🎉 Successfully passed the Ph.D. thesis defense!
- 2025.07: 🎉🎉 GRIP is accepted by PUT at ICML 2025!
- 2025.04: 🎉🎉 Passed the Ph.D. proposal!
- 2025.01: 🎉🎉 GOFA is accepted by ICLR 2025!
- 2024.09: 🎉🎉 GNN4TaskPlan is accepted by NeurIPS 2024! Congratulations to Xixi and Yifei!
- 2024.08: Check out our newest work on joint modeling of graph and language (paper, code). In this work, we propose GOFA, which interleaves GNN layers into LLMs to equip them with the ability to reason on graphs. We also design multiple novel large-scale unsupervised pretraining tasks for GOFA. GOFA achieves SOTA results across multiple benchmarking datasets!
- 2024.06: We release TAGLAS, an atlas of text-attributed graph datasets. We provide easy-to-use APIs for loading datasets, tasks, and evaluation metrics. The technical report is available on arXiv. The project is still in development, and any suggestions are welcome.
- 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
GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models
Jiarui Feng, Donghong Cai, Yixin Chen, Muhan Zhang
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts
Jiarui Feng, Hanqing Zeng, Karish Grover, Ruizhong Qiu, Yinglong Xia, Qiang Zhang, Qifan Wang, Ren Chen, Dongqi Fu, Jiayi Liu, Zhoukai Zhao, Xiangjun Fan, Benyu Zhang, Yixin Chen
GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
Lecheng Kong*, Jiarui Feng*, Hao Liu*, Chengsong Huang, Jiaxin Huang, Yixin Chen, Muhan Zhang (* Equal contribution)
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 on Google Scholar.
🎖 Honors and Awards
- 2023.10: NeurIPS 2023 Travel Award.
- 2021.07: ICIBM 2021 Travel Award.
📖 Educations
- 2021.09 - 2026.02: Ph.D., Washington University in St. Louis, MO, USA.
- 2019.09 - 2021.05: M.S., Washington University in St. Louis, MO, USA.
- 2015.09 - 2019.06: B.S., South China University of Technology, Guangzhou, China.
💻 Internships
- 2025.09 - 2025.12: Student Researcher, Meta, Remote, US.
- 2025.05 - 2025.08: Research Intern, Meta, Menlo Park, US.
- 2024.06 - 2024.09: Lab Research Intern, Pinterest, Remote, US.
- 2019.06 - 2019.08: SWE Intern, Alibaba Cloud, Hangzhou, China.
- 2018.12 - 2019.02: Data Analytics Intern, Credit Card Center, Guangzhou Bank, Guangzhou, China.
🔬 Services
- Conference reviewer: CVPR23; NeurIPS23; ICLR24; CVPR24; NeurIPS24; ICLR25; ICML25; CVPR25; NeurIPS25; ICLR26.
🎮 Misc
- Crazy computer gamer: Overwatch, Apex Legends, World of Warcraft, PUBG, CS:GO…
- I have a cute ragdoll called $\theta$, and I love him!!!