Jingzhe Liu

Ph.D. Student · Michigan State University
Advised by Prof. Jiliang Tang
Previous B.S. from Shanghai Jiao Tong University

My research focuses on enhancing LLMs and agents with stronger personalization capabilities, enabling machine learning systems to better understand, adapt to, and support people.

“I know that I know nothing.”

“Know thyself.” —Socrates

CV Email Scholar GitHub LinkedIn

Education

Michigan State University

Ph.D. Student · 2023 ~ Present

Computer Science and Engineering · Advisor: Prof. Jiliang Tang

Shanghai Jiao Tong University

B.Eng. · 2019 ~ 2023

Electronic and Computer Engineering

Work Experience

Snapchat

May ~ Sep 2026

Research Intern · User Modeling and Personalization Team · Agentic Retrieval

Snapchat

May ~ Sep 2025

Research Intern · User Modeling and Personalization Team · Generative Recommendation

Selected Publications

Filter by research area.

Beyond Fixed Depths and Widths: Optimizing Textual Decoding Tries in LLM-based Generative Recommendation

Jingzhe Liu, Hanbing Wang, Liam Collins, Jiliang Tang, Tong Zhao, Neil Shah, Mingxuan Ju.

RecSys 2026 - 20th ACM Conference on Recommender Systems.

Recommendation

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View

Jingzhe Liu, Liam Collins, Jiliang Tang, Neil Shah, Tong Zhao, Mingxuan Ju.

KDD 2026 - ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

Recommendation Scaling

Higher-order Structure Boosts Link Prediction on Temporal Graphs

Jingzhe Liu, Zhigang Hua, Yan Xie, Bingheng Li, Harry Shomer, Yu Song, Kaveh Hassani, Jiliang Tang.

SDM 2026 - SIAM International Conference on Data Mining.

Temporal Graphs

Towards Neural Scaling Laws on Graphs

Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang.

LOG 2024 - Learning on Graphs Conference.

Graphs Scaling

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang.

NeurIPS D&B Track 2024 - Dataset and Benchmark Track.

Graphs Foundation Models Benchmark

A Pure Transformer Pretraining Framework on Text-attributed Graphs

Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu.

LOG 2024 - Learning on Graphs Conference.

Graphs Foundation Models

Do Neural Scaling Laws Exist on Graph Self-Supervised Learning?

Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma.

LOG 2024 - Learning on Graphs Conference.

Graphs Scaling

Honors And Awards

SDM Doctor Student Travel Award

2025

Outstanding Graduate in Shanghai Jiao Tong University

2023

Silver Award in Capstone Design of Shanghai Jiao Tong University

2023

Yu Liming Scholarship

2021

Jiong Wu & Jie Sun Sunshine Scholarship

2020