Po-wei Chi is a senior research engineer based in Austin with six years of experience applying machine learning and statistical analysis to semiconductor and hardware-focused problems. At AMD he progressed from Design Engineer to Senior Research Engineer, building domain-specific deep learning solutions and deploying them on cloud infrastructure and LSF for cross-functional teams. His background includes hands-on image-processing and Mask R-CNN work for wafer defect detection at TSMC, plus practical deployment experience using Docker and internal CI workflows. He combines an MS in Electrical and Computer Engineering from UC Davis with a pragmatic engineering approach that bridges research prototypes and production-ready systems. Known for translating industrial data into targeted ML models, he often pairs classical statistical methods with modern deep learning to solve noisy, domain-specific problems. He favors solutions that are reproducible and deployable, reflecting both research rigor and production constraints.
6 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Electrical and Computer Engineering, Master of Science - MS, Electrical and Computer Engineering at University of California, Davis
Bachelor of Science - BS, Electical Engineering, Bachelor of Science - BS, Electical Engineering at National Chiayi University
Efficient few-shot learning with Sentence Transformers
Contributions:48 pushes, 9 branches in 2 years 2 months
pytorchnlpsentencetransformersbert
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