Qi W
MLE at Uber
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolQi W is a machine learning engineer with nine years of experience applying Bayesian inference, AutoML, recommendation and ranking systems to high-impact industrial problems across Uber, J.P. Morgan and Siemens. He holds a PhD in machine learning (Best Thesis Award) and a strong academic background in statistical signal processing, which he blends with production-focused work in marketplace pricing, optimization and anomaly detection. Comfortable across probabilistic modeling, time series and computer vision, he bridges research-grade methods (MCMC, variational inference) with scalable ML pipelines. Notably, he has transitioned research on inverse problems and generative models into practical solutions for trading and mobility marketplaces. Based in the NYC area, he is a pragmatic problem-solver who emphasizes “learn to learn” and getting things done.
9 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree, Electrical and Electronics Engineering, GPA: 87.19/100 Rank: 7/156, Bachelor’s Degree, Electrical and Electronics Engineering, GPA: 87.19/100 Rank: 7/156 at Beihang UniversityMaster Exachange, Bayesian Sequential Signal Processing, Master Exachange, Bayesian Sequential Signal Processing at UPC - ETSETB TelecomBCNDoctor of Philosophy (Ph.D.), Machine Learning, Best Thesis Award at University of Toulouse (Prix Léopold Escande), Doctor of Philosophy (Ph.D.), Machine Learning, Best Thesis Award at University of Toulouse (Prix Léopold Escande) at Institut national polytechnique de Toulouse
English, French, Chinese
Github Skills (9)
hierarchical6
autoencoder5
classification5
segmentation5
pointnet5
deep-learning3
computer-vision3
point-cloud3
pytorch2
Programming languages (1)
Github contributions (5)
qw245/FUMI
Aug 2016 - Nov 2016
Contributions:6 commits, 8 pushes, 1 branch in 3 months
qw245/BlindFuse
Sep 2016 - Sep 2016
Contributions:4 commits, 5 pushes, 1 branch in 2 days
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