I am a postdoc at Michigan State University (MSU), and fortunately work with Prof. Jiliang Tang. Before that, I got my Ph.D. degree from the Department of Artificial Intelligence at Jilin University, working with Prof. Yi Chang.

My research interests focus on developing efficient, trustworthy, and application-driven machine learning algorithms, particularly in Graph Learning, Information Retrieval, and AI for Science.

Email: guokai1 at msu.edu

News

Apr. 2025: Our paper “Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach” is accepted by ACL-Main! [pdf]

Mar. 2025: New preprint - “Empowering GraphRAG with Knowledge Filtering and Integration” [pdf]

Mar. 2025: One paper on AI for Science, titled “Aligning Large Language Models and Geometric Deep Models for Protein Representation”, has been accepted by Cell Patterns journal. [pdf]

Feb. 2025: New preprint studying the effectiveness of RAG vs. GraphRAG [pdf]

Jan. 2025: New survey on Retrieval-Augmented Generation (RAG) with Graphs [pdf]

Jul. 2024: New preprint - “Learning on Graphs with Large Language Models (LLMs): A Deep Dive into Model Robustness” [pdf]

May. 2024: One paper accepted by KDD, 2024. [pdf]

Jun. 2023: Begin my visiting at MSU！

Apr. 2023: One paper accepted by ICML, 2023 [pdf]

Jun. 2022: One paper accepted by AAAI, 2022 (Oral 4.5%) [pdf]

Selected publication

Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach
Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu.
ACL, 2025 (Corresponding Author)

Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective
Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang.
KDD, 2024.

Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships
Yaming Guo*, Kai Guo*, Xiaofeng Cao, Tieru Wu, Yi Chang.
ICML, 2023

Orthogonal graph neural networks
Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang.
AAAI, 2022 (Oral)

Service

PC members, and reviewers for multiple journals and international conferences in machine learning and data science such as TPAMI, TKDD, TKDE, KDD, NeurIPS and ICLR.