Tianqi Chen
About
I am interested in the intersection of machine learning and systems. The real excitement of this area comes from what can enable when we bring advanced learning techniques and system together. On that end, I am also pushing the direction on deep learning, knowledge transfer and lifelong learning. I am a believer of open source and open science. My research involves publishing algorithms in openly accessible mediums and building open-source machine learning systems that are widely adopted. Here are the ML systems that I created: Apache TVM, an Automated End-to-End Optimizing Compiler for Deep Learning. XGBoost, a scalable tree boosting system. Apache MXNet(co-creator)
Research Performance Summary
First Recorded Paper
Transfer learning for behavioral targeting
Year: 2010
Citations: 12
Venue: Proceedings of the 19th international conference on World wide web
Latest Recorded Paper
XGrammar 2: Dynamic and Efficient Structured Generation Engine for Agentic LLMs
Year: 2026
Citations: 0
Venue: arXiv preprint arXiv:2601.04426
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.