Yawei Luo - Data Scientist

Yawei Luo

Data Scientist

Atlanta Metropolitan Area United States

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Summary

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Senior

🎓

Top School

Yawei Luo is a data scientist with nine years of professional experience who blends consumer banking expertise with advanced analytics, currently applying ML and NLP at FIS after earning an MS in Data Science and Analytics from Georgia State University. She has led applied projects that turned social media sentiment into actionable insights for Truist’s mortgage team and quantified emissions tradeoffs for automotive clients using predictive modeling. Her background in economics and organizational management, plus hands-on banking roles, gives her a strong product-minded perspective on customer behavior and risk. Yawei pairs classical regression and classification work with deep learning and a growing interest in computer vision, evidenced by her GitHub focus. She is practiced at production-oriented data cleaning, cross-team communication, and mentoring, having managed project cadences in academic-industry sprints and trained branch staff in banking operations. Colleagues describe her as analytical, customer-centered, and adept at turning messy financial and social data into clear, business-ready recommendations.

9 years of coding experience

2 years of employment as a software developer

Bachelor’s Degree, Economics, Organizational Management, Dance, 3.80, Bachelor’s Degree, Economics, Organizational Management, Dance, 3.80 at Agnes Scott College

Master of Science - MS, Data Science and Analytics, Master of Science - MS, Data Science and Analytics at Georgia State University

Post Bacc, Information Technology, A, Post Bacc, Information Technology, A at Georgia Gwinnett College

English, Chinese

Github Skills (27)

shift10

image-translation10

semantics10

adversarial-learning10

few-shot-learning10

transfer-learning10

adaptation10

semi-supervised-learning9

paper9

segmentation9

mining9

pytorch8

deep-learning7

scene6

dynamic-feature5

Programming languages (2)

C++Python

Github contributions (5)

RoyalVane/CLAN

Apr 2019 - Mar 2021

( CVPR2019 Oral ) Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation

Contributions:45 commits, 2 PRs, 43 pushes in 1 year 11 months

pytorchcvpr2019-orallookshiftdeep-learning

RoyalVane/ASM

Oct 2020 - Jul 2021

( NeurIPS 2020 ) Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation

Contributions:43 commits, 2 PRs, 40 pushes in 8 months

pytorchminingneurips-2020one-shotdeep-learning

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