Shih-feng Yang
Machine Learning Scientist at Expedia Group
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolShih-feng Yang is a Machine Learning Scientist with 11 years of experience applying deep learning and ML pipelines to natural language understanding, sequential data prediction, and large-scale experimentation. He holds a PhD from Purdue and blends research rigor with production engineering, having built end-to-end ML systems from feature engineering to deployment and model tracking at Intel and now personalization and LLM-driven marketing at Expedia. His work spans CPU/AI performance analysis, manufacturings’ predictive analytics, and fraud/forensics-style NLU research, demonstrating an uncommon ability to translate domain signals (including hardware counters) into actionable models. Proficient across Python, C/C++, Java, PyTorch and TensorFlow, he also architects scalable data systems and real-time caching for robust ML services. Based in Seattle, he pairs academic publications and lab experience with practical software delivery—his GitHub reflects a mix of research and production-oriented projects stemming from his AKRaNLU lab background. Colleagues rely on him to bridge model research and operational impact, turning complex experimental insights into measurable business outcomes.
11 years of coding experience
8 years of employment as a software developer
Master of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at National Central UniversityDoctor of Philosophy - PhD Computer and Information Sciences General, Doctor of Philosophy - PhD Computer and Information Sciences General at Purdue University
Chinese, English
Github Skills (5)
twitter8
pos8
tagging7
deep-learning5
pytorch5
Github contributions (5)
tomelf/CNIT623-Native-Language-Identification-On-English-Learner-Dataset
Mar 2018 - Apr 2018
Contributions:27 commits, 2 PRs, 23 pushes in 1 month
dataseteslnationalityauthorsidentify
NLT-Conversation/Argument-Stance-Classification
Nov 2017 - Dec 2017
Contributions:13 commits, 6 PRs in 18 days
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