Ben Vo
Applied Scientist at Amazon
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolBen Vo is an applied scientist with a PhD in Computer Science and a decade of experience building large-scale ML and NLP systems, now applying LLMs and RAG at Amazon in the San Francisco Bay Area. He has driven measurable business impact—deploying student models distilled from LLMs and semantic ranking features that produced statistically significant relevance and engagement gains and multimillion-dollar revenue influence at Walmart Search. His research background includes EMNLP, SIGIR and EACL papers on multimodal neural search, fact-checking, and fake-news detection, bridging top-tier academic rigor with production engineering. Comfortable across Python/PyTorch and production pipelines, he blends deep algorithmic knowledge with pragmatic A/B-tested delivery. Colleagues value his persistence and resilience; less obvious is his knack for translating complex research (e.g., knowledge distillation) into team-wide frameworks that accelerate adoption.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Utah State UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Worcester Polytechnic Institute
Vietnamese, English
Github Skills (50)
pytorch10
python10
attention-mechanism10
audio10
fact-checking10
deep-learning10
tensorflow10
deep-neural-networks10
natural-language-processing10
nlp10
transformers9
text-generation9
fact9
data-repository9
llm9
Programming languages (3)
Github contributions (5)
nguyenvo09/LearningFromFactCheckers
Apr 2019 - Dec 2021
Repository for Learning from Fact-checkers: Analysis and Generation of Fact-checking Language, accepted as a full paper by SIGIR 2019.
Contributions:1 release, 31 commits, 29 pushes in 2 years 8 months
pytorchnlpfactcheckingfact-checking
nguyenvo09/fake_news_detection_deep_learning
Feb 2018 - Nov 2018
Fake News Detection using Deep Learning models in Tensorflow
Contributions:63 commits, 5 PRs, 53 pushes in 8 months
deep-learningtensorflowdeep-neural-networksattention-mechanismfake-news
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