Jifan Chen
Applied Scientist at Amazon Web Services (AWS)
Austin, Texas, United States
Summary
👤
Senior🎓
Top SchoolJifan Chen is an Applied Scientist with a decade of experience bridging academic research and industry, currently at AWS after completing a Ph.D. in Computer Science at UT Austin under Prof. Greg Durrett. His work focuses on natural language processing, especially model decomposition and verification, with applied stints improving table-to-text generalization at AWS and enhancing QA robustness at Google. He brings deep expertise in making NLP models more interpretable and reliable, translating theoretical advances into practical system improvements. Trained at Fudan University and seasoned by high-impact internships, he blends rigorous research methodology with product-minded experimentation. Colleagues describe him as quietly curious—his Github motto "Stay young, stay simple" reflects a pragmatic, refreshingly minimal approach to complex problems.
11 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of Texas at AustinBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Fudan University
Chinese, English
Github Skills (35)
python9
natural-language-processing9
nlp9
deep-learning8
fasttext8
lda8
topic-modeling8
pytorch8
data-science8
word2vec8
data-mining7
word-embeddings7
information-retrieval7
corpus7
gensim7
Programming languages (1)
Github contributions (5)
jifan-chen/QA-Verification-Via-NLI
Sep 2021 - Nov 2022
Code and dataset for the EMNLP 2021 Finding paper "Can NLI Models Verify QA Systems’ Predictions?"
Contributions:8 commits, 8 pushes, 1 branch in 1 year 2 months
jifan-chen/subquestions-for-fact-checking
May 2022 - Nov 2022
Code and dataset for the paper: Generating Literal and Implied Subquestions to Fact-check Complex Claims
Contributions:6 commits, 5 pushes, 1 branch in 6 months
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