Tianshu Yu
Member Of Technical Staff at Liquid AI
San Jose, California, United States
Summary
👤
Senior🎓
Top SchoolTianshu Yu is a software engineer with 10 years of experience specializing in scalable reinforcement learning and high-performance inference infrastructure for large multimodal models and autonomous agents. Based in San Jose, he has shipped production-grade systems at ByteDance that scaled GRPO training of a 235B MoE model across 128 H100s, improved MFU by 5×, and introduced async pipeline parallelism and custom inference engines to enable true on-policy RL at trillion-parameter scale. His background includes an MS in Quantum Computing from Duke and a strong foundation in mathematical reasoning, which he leverages to optimize kernels, parallel methods, and hardware bottlenecks. Now at Liquid AI, he continues to focus on infrastructure that advances towards AGI/ASI, blending research-grade rigor with pragmatic systems engineering. Notably, he often combines low-level GPU profiling (NSYS/NCU) with algorithmic changes to unlock order-of-magnitude improvements in throughput and latency.
10 years of coding experience
2 years of employment as a software developer
Master of Science - MS Quantum Computing, Master of Science - MS Quantum Computing at Duke UniversityBachelor's degree Mathematics, Bachelor's degree Mathematics at Indiana University Bloomington
Chinese, English
Stackoverflow
11reputation
46reached
0answers
1question
Github Skills (14)
scs10
shortest-path6
algorithm6
text-based6
breadth-first-search6
dijkstra6
image-processing5
segmentation5
image-segmentation5
semantic-segmentation5
computer-vision4
instance-segmentation2
pytorch1
anchor1
Programming languages (2)
Github contributions (5)
yuts21/dns-server
May 2020 - Jul 2021
Contributions:3 pushes, 1 branch in 1 year 2 months
iCVTEAM/PFSNet
Sep 2021 - Dec 2021
Contributions:2 commits, 2 pushes in 2 months
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