David Dai
Mountain View, California, United States
Summary
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SeniorDavid Dai is a software engineer with eight years of experience building scalable backend systems and AI-enabled features across Google, YouTube, and Google Labs, based in Mountain View. He has driven product-impacting work from end-to-end—designing YouTube's virtual currency infrastructure and unifying abuse-reporting APIs, to shipping on-device intent-detection models and multi-channel integrations for Assistant/Gemini. Comfortable across full-stack, data pipelines, and ML deployment, he blends product sensibility with rigorous engineering to translate metrics and cohorts into practical features and monitoring. His background includes research in multimodal EEG emotion classification and building cost-saving NLP chatbots in industry, revealing a mix of academic curiosity and production focus. David’s approach—“keep learning, keep developing”—is reflected in cross-team collaboration with product and legal partners and a track record of measurable uplifts (e.g., 10.8% CTR improvement).
8 years of coding experience
Github Skills (22)
deap9
eeglab8
matlab7
mindwave6
classification6
keras5
emotion5
python5
machine-learning4
css4
deep-learning4
tensorflow4
django3
headset3
react3
Programming languages (5)
Github contributions (5)
dweidai/Text-Arousal-and-Valence-Classification
May 2019 - Jun 2019
Contributions:42 commits, 41 pushes, 1 branch in 26 days
dweidai/DEAP-JRP-Emotion-Classification
Apr 2019 - Jul 2020
Emotional Classification with the DEAP dataset using EEGLAB, matlab and python. Currently in the status of developing a more efficient and high accuracy method for emotion classification using EEG data regardless of number of channels.
Contributions:21 commits, 2 PRs, 16 pushes in 1 year 3 months
pythondevelopinghigh-accuracydeap-datasetchannels
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