Lizhu Zhang
AI Research Scientist Director at Meta, working on LLMs and RecSys
I am an AI Research Scientist Director at Meta. Before Meta, I worked on recommender systems and distributed systems at Twitter/X, Uber, Google, and VMware. My research spans reinforcement learning, causal inference, auto-research, and model paradigm innovation across RecSys and LLMs.
I feel fortunate to work alongside some of the brightest minds in the field, exploring the frontiers of AI together.
I received my bachelor’s degree in Physics and my master’s degree in Electrical Engineering from Tsinghua University, where I was advised by Dr. Yu Zheng.
news
| May 15, 2026 | Two papers accepted to ACL 2026 — Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understanding (Main Conference) and TARo: Token-level Adaptive Routing for LLM Test-time Alignment (Findings). |
|---|---|
| May 01, 2026 | Paper Token-Level LLM Collaboration via FusionRoute accepted to ICML 2026. |
| Mar 15, 2026 | Paper StreamMem: Query-Agnostic KV Cache Memory for Streaming Video Understanding accepted to a CVPR 2026 Workshop (VidLLMs). |
selected publications
* indicates corresponding / joint last authorship. | full list →
2026
2025
2011
- TWEBRecommending friends and locations based on individual location historyACM Transactions on the Web, 2011
2009
- WWWMining interesting locations and travel sequences from GPS trajectoriesIn Proceedings of the 18th International Conference on World Wide Web (WWW), 2009
- GISMining correlation between locations using human location historyIn Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), 2009