Tianqi Chen
Assitant Professor at NVIDIA
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top School
Top expert inHigh-Performance Machine Learning Computing
Tianqi Chen is a Distinguished Engineer and academic with 12 years of experience building high-performance machine learning systems and compilers, currently based in Seattle. He combines deep research in ML, data mining, and stochastic processes with hands-on systems engineering—co-founding OctoML and contributing foundational code to widely used open-source projects like XGBoost, TVM, MXNet, and DLPack. His work spans low-level distributed runtime and I/O, neural network compilers, and efficient inference—frequently touching core libraries used across Python, R, C++ and accelerator backends. As an assistant professor at Carnegie Mellon and a former UW PhD, he moves fluently between research and production, shipping optimizations for MPI-backed distributed training and GPU-accelerated execution. Notably, he helped implement core primitives in projects that underpin modern ML stacks (e.g., XGBoost’s rabit engine and TVM’s TIR), showing a rare blend of numerical, systems, and ML expertise. He is known for pragmatic, performance-first contributions that make large-scale ML both faster and more portable.
12 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of WashingtonMaster of Science (MS), Computer Science, Master of Science (MS), Computer Science at Shanghai Jiao Tong University
Github Skills (65)
graph-algorithms10
operation10
c1110
c1710
lua10
deep-learning10
parallel-computing10
webgpu10
cpp10
javascript10
convolutional-neural-networks10
memory-management10
neural-network10
typescripts10
tensor10
Programming languages (20)
Github contributions (5)
mlc-ai/mlc-llm
Apr 2023 - Mar 2025
Universal LLM Deployment Engine with ML Compilation
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 381 reviews, 745 PRs in 1 year 10 months
Contributions summary:Tianqi's primary contribution is the addition of a command-line interface (CLI) feature to the project, specifically a "stats" command. This feature allows users to view statistics from the latest round of conversation within the application. The implementation included modifications to the `cpp/cli_main.cc` file to incorporate the new command and its functionality, utilizing functions from the project’s chat module. The user also added support for loading and using external tokenizer libraries.
language-modelllmmachine-learning-compilationtvm
dmlc/dmlc-core
Mar 2015 - Oct 2020
A common bricks library for building scalable and portable distributed machine learning.
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 release, 4 reviews, 403 commits in 5 years 7 months
Contributions summary:Tianqi primarily worked on the I/O components of the `dmlc-core` library. Their contributions involved implementing interfaces for stream I/O, including `IStream`, `ISeekStream`, and `InputSplit`. The user created specific implementations like `FileStream`, `HDFSStream`, and `LineSplitter`, and refactored existing code to accommodate changes, added endian aware serialization, and allowed support for text format data for the IO system. The user also worked on refactoring of the parser with more performance
scalablebricksmachine-learningportabledistributed-machine-learning
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