夏鲁豫 

算法工程师 at 大箴(杭州)科技有限公司

Hangzhou City, Zhejiang, China
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts

Summary

👤
Senior
🎓
Top School
夏鲁豫 is an experienced algorithm engineer based in Hangzhou with a decade of hands-on work in NLP and machine learning across startups and research-driven companies. He has progressed from software engineering and ML roles into his current position at 大箴(杭州)科技有限公司, applying practical engineering to NLP model development and deployment. Notably, he contributed to the well-known gluon-nlp repository by adding Chinese and multilingual BERT models, tokenizers, and a SQuAD 2.0 dataset integration—skills that underline both applied research and production-ready pipelines. His background blends model engineering, tokenizer/data-pipeline integration, and question-answering systems, making him effective at turning research models into usable products. Colleagues would describe him as persistent and curious—aptly reflected by his personal motto about continuous exploration—which shows through steady contributions to open-source and cross-company NLP projects.
code10 years of coding experience
book学士, 计算机科学与技术, 学士, 计算机科学与技术 at Zhengzhou University
github-logo-circle

Github Skills (11)

machine-learning10
nlp10
gluon10
python10
natural-language-processing10
bert10
mxnet9
deeplearning-ai9
deep-learning9
natural-language-understanding8
natural-language-generation7

Programming languages (15)

C#JavaC++CRustVueGoHTML

Github contributions (5)

github-logo-circle
dmlc/gluon-nlp

Dec 2018 - Feb 2019

NLP made easy
Role in this project:
userML Engineer
Contributions:5 commits, 7 PRs, 50 comments in 2 months
Contributions summary:夏鲁豫 primarily focused on enhancing the repository's natural language processing capabilities. Their contributions included the addition of Chinese and multilingual BERT models, accompanied by the implementation of corresponding tokenization strategies and related updates to model configurations. They also integrated a BERT tokenizer into the existing data transformation pipeline and introduced a dataset for SQuAD 2.0, signifying a focus on question answering tasks.
nlpmxnetnatural-language-understandingnlgnatural-language-generation
Contributions:3 commits, 2 pushes, 1 branch in 1 day
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
夏鲁豫 - 算法工程师 at 大箴(杭州)科技有限公司