Zhilin Wang
Applied Scientist at NVIDIA
United States
Summary
🤩
Rockstar🎓
Top SchoolZhilin Wang is an applied scientist with 8 years’ experience building conversational AI and education-focused NLP systems, currently leading development of task-oriented dialogue and QA research frameworks at NVIDIA that sped training and deployment over 4x. He combines strong academic grounding (MSc in Computational Linguistics from UW, BA from Cambridge) with practical product experience—from improving Alexa’s reference resolution by 80% at Amazon to contributing dialogue-state tracking refactors in the popular NVIDIA NeMo open-source project. Zhilin’s work sits at the intersection of NLP, psychology, and education: he has founded edtech startups that served tens of thousands of students and researched personalized dialogue and commonsense integration to boost NLU performance. Comfortable bridging research and production, he has a track record of shipping scalable ML systems and translating classroom learning challenges into deployable NLP solutions.
8 years of coding experience
3 years of employment as a software developer
Master's degree, Computational Linguistics, 4.0/4.0, Master's degree, Computational Linguistics, 4.0/4.0 at University of WashingtonBachelor's degree, Education, Psychology and Learning, Bachelor's degree, Education, Psychology and Learning at University of CambridgeA levels, BCME H1 History, A levels, BCME H1 History at Raffles Institution
Github Skills (8)
nlp10
deep-learning10
large-language-models10
python10
generative-ai10
pytorch9
machine-translation8
asr8
Programming languages (3)
Github contributions (5)
NVIDIA/NeMo
Jan 2022 - Jan 2023
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Role in this project:
ML Engineer
ML EngineerContributions:170 reviews, 85 commits, 91 PRs in 11 months
Contributions summary:Zhilin primarily contributed to refactoring and improving dialogue state tracking functionalities within the NVIDIA NeMo framework. Their work involved modifying code related to dialogue state tracking for better dataset interoperability, including the addition of compatibility with an assistant dataset. They also made several style and typo fixes, updated Jenkinsfiles, and addressed review requests, demonstrating an understanding of the project's codebase and development workflow.
asrspeech-recognitionnatural-language-processingttsspeaker-diarization
Zhilin123/Publications
Sep 2019 - Nov 2021
Contributions:36 pushes, 1 branch in 2 years 2 months
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.