Wei Tan
Senior Quantitative Researcher
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolWei Tan is a Senior Quantitative Researcher at Citadel with a decade of experience building high-performance ML systems for quantitative trading, specializing in GPU acceleration, distributed training, and scalable inference. He brings a rare combination of deep research pedigree—PhD from Tsinghua and prior roles at IBM and the University of Chicago/Argonne—with hands-on engineering that optimizes Spark and GPU stacks for low-latency, production-grade workflows. As an IEEE Associate Editor and former IBM Research Staff Member, he blends academic rigor with practical performance tuning across HPC and distributed systems. Known for translating complex scientific workflows into resilient, high-throughput pipelines, he often focuses on the infrastructure side of ML problems that others treat as purely algorithmic. Based in Chicago, he thrives at the intersection of machine learning, systems engineering, and quantitative finance.
10 years of coding experience
3 years of employment as a software developer
Bachelor Automation, Bachelor Automation at Tsinghua University
Chinese, English
Github Skills (18)
als9
cuda6
gpu6
kernel4
branches4
spark3
apache-spark3
machine-learning3
apache2
factorization2
yahoo2
big-data1
pdf1
matrix1
opencl1
Github contributions (5)
cuMF/cumf_als
Apr 2016 - Mar 2017
Contributions:52 commits, 1 PR, 44 pushes in 11 months
cudagpualsgpus
wei-tan/wei-tan.github.io
Apr 2016 - Jul 2021
Contributions:32 pushes, 1 branch in 5 years 3 months
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