Ting-wu Chin - Quantitative Researcher

Ting-wu Chin

Quantitative Researcher

Miami, Florida, United States

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Summary

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Senior

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Top School

Ting-wu Chin is a quantitative researcher with 11 years of engineering and research experience, currently applying deep learning and optimization expertise at Citadel Securities after completing a Ph.D. at Carnegie Mellon focused on efficient, resource-constrained convolutional neural networks. He has a strong track record of turning research into practical speedups—e.g., an 8x faster model compression method during a Microsoft internship and a 20x performance improvement on a face-swap system—alongside multiple research internships at Facebook AI and Reality Labs. Equally comfortable in academia and industry, he combines rigorous theoretical work with hands-on systems engineering across model pruning, quantization, and deployment. Based in Miami, he maintains an active research homepage and GitHub that reflect a sustained focus on Pareto-efficient model design and real-world performance gains.

11 years of coding experience

2 years of employment as a software developer

Master of Science (M.S.), Computer Science, 4.3/4.3, Master of Science (M.S.), Computer Science, 4.3/4.3 at National Chiao Tung University

Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at Carnegie Mellon University

English, Chinese

Github Skills (77)

caffe9

matlab8

efficientnet8

deep-learning8

machine-learning8

facebook-clone8

face7

model-compression7

android7

pytorch7

resnet6

slurm6

computer-vision6

python6

convolutional-neural-networks6

Programming languages (5)

JavaC++CHTMLPython

Github contributions (5)

enyac-group/Renofeation

Feb 2020 - Jun 2021

Contributions:3 commits, 1 push, 1 branch in 1 year 4 months

enyac-group/LeGR

Apr 2019 - Mar 2020

Contributions:15 commits, 3 pushes, 1 branch in 10 months

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