Taejin Park
Sr, Research Scientist at NVIDIA
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTaejin Park is a senior research scientist based in San Jose with 10 years of experience applying signal processing, machine learning, and deep learning to speech AI. At NVIDIA he advances NeMo ASR and enterprise speech products, contributing GPU-optimized modules and improved speaker counting for diarization in a widely used open-source framework. His background spans academia (PhD research at USC) and industry internships at Microsoft and Amazon focused on speech and dialogue systems, giving him both theoretical depth and product-oriented experience. Earlier work at ETRI and capio.ai anchored his expertise in audio watermarking, event detection, and ASR-integrated diarization pipelines. Taejin blends rigorous research with production engineering, uniquely able to turn advanced speech models into scalable components for real-world applications.
10 years of coding experience
9 years of employment as a software developer
Bachelor's degree, Electrical and Electronics Engineering, Bachelor's degree, Electrical and Electronics Engineering at Seoul National UniversityMaster's degree, Computer Science, Master's degree, Computer Science at University of Southern California
Korean, English
Github Skills (15)
pytorch10
machine-learning10
python10
clustering-algorithm10
speech-recognition9
gpu-programming9
deep-learning8
tensor8
audio-processing8
speaker-diarization8
neural-network8
asr8
generative-ai8
large-language-models8
tensorflow8
Programming languages (3)
Github contributions (5)
NVIDIA/NeMo
Jul 2021 - 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:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:589 reviews, 366 commits, 144 PRs in 1 year 6 months
Contributions summary:Taejin contributed to the `nvidia/nemo` repository, a generative AI framework. Their work focused on improving the `nmse_clustering` module, which is used for speaker diarization. The commits involved updating the code to run on the GPU, fixing bugs, adding docstrings, and making style improvements. The user also enhanced speaker counting for short audio recordings, which includes the addition of anchor embeddings.
asrspeech-recognitionnatural-language-processingttsspeaker-diarization
tango4j/tensorflow-vs-pytorch
Feb 2018 - Jun 2019
Contributions:90 commits, 133 pushes, 1 branch in 1 year 4 months
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