YifanĀ Ding
Applied Scientist at Amazon
Notre Dame, Indiana, United States
Summary
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Top SchoolYifan Ding is an applied scientist with nine years of experience who completed a Ph.D. in Computer Science and Engineering at the University of Notre Dame and now works on large-scale ML at Amazon. His research over three-plus years centers on text mining, named entity recognition, entity linking, and distributed deep learning, bridging rigorous academic methods with production-focused solutions. Multiple Amazon internships preceded his full-time role, giving him hands-on experience taking models from research prototypes to deployed services. With a background in physical chemistry and a master's in chemistry & biochemistry, he brings a quantitative, cross-disciplinary approach to NLP problems that often uncovers domain-specific signal others miss. Based in Notre Dame, Indiana, he combines deep academic training with practical engineering at scale, focusing on robust, distributed model architectures.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science (B.Sc.), Physical Chemistry, Bachelor of Science (B.Sc.), Physical Chemistry at University of Science and Technology of ChinaDoctor of Philosophy - PhD, Computer Science and Engineering, Doctor of Philosophy - PhD, Computer Science and Engineering at University of Notre Dame
Chinese, English
Github Skills (61)
transformers10
pytorch10
language-model10
python10
machine-learning10
deep-learning10
tensorflow10
natural-language-processing10
bert10
heterogeneous10
transformer10
speech-recognition10
nlp10
jax10
translation9
Programming languages (3)
Github contributions (5)
yifding/hetseq
Feb 2020 - Apr 2021
HetSeq: Distributed GPU Training on Heterogeneous Infrastructure
Contributions:1 release, 267 commits, 6 PRs in 1 year 2 months
cudaheterogeneousgpuinfrastructuredistributed-training
yifding/deep_ed_PyTorch
Nov 2021 - Nov 2022
Contributions:23 commits, 18 pushes, 1 branch in 11 months
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