Phu Htut
Principal Applied Scientist at Oracle
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolPhu Htut is a Principal Applied Scientist with a decade of experience building and safeguarding large-scale NLP and foundational model systems, currently at Oracle after leading applied science efforts at AWS. He holds a PhD candidacy in Data Science from NYU and has deep expertise in natural language understanding, model fine-tuning for RAG, machine translation, and conversational AI. At AWS he worked on Bedrock protections and productionized LLM finetuning, and his research background includes collaborations with FAIR and hands-on contributions to the widely used jiant NLP toolkit (implementing PRPN integration). Comfortable bridging research and production, he has a proven track record of shipping robust ML features at cloud scale and updating complex model dependencies. Fluent in both academic and industry settings, he also brings experience teaching core NLP courses at NYU and mentoring engineers. A Singapore-educated engineer with international research internships, he combines rigorous modeling skills with practical deployment know-how.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Data Science, Doctor of Philosophy - PhD Data Science at New York UniversityUniversity of California, Los AngelesBachelor of Engineering (BEng) Computer Science(Information Systems focus), Bachelor of Engineering (BEng) Computer Science(Information Systems focus) at Nanyang Technological University Singapore
Github Skills (5)
transformers10
pytorch10
nlp10
python10
bert9
Programming languages (2)
Github contributions (5)
nyu-mll/jiant
Apr 2019 - Feb 2021
jiant is an nlp toolkit
Role in this project:
ML Engineer
ML EngineerContributions:29 commits, 11 PRs, 107 pushes in 1 year 9 months
Contributions summary:Phu made significant contributions to the `jiant` project, an NLP toolkit, by adding code for the PRPN model, a parsing-reading-predict network, and integrating it with existing modules. Their work included implementing PRPN-related functionalities, fixing conflicts, and updating configurations. Furthermore, they also updated other related dependencies within the model.
nlptransformersmultitask-learningsentence-representationbert
nyu-mll/nlu-test-sets
Dec 2020 - Jul 2021
Contributions:65 commits, 1 push, 4 comments in 7 months
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