Cheng-ping Hsieh
NeMo (LLM Long Context) - Applied Research Scientist at NVIDIA
United States
Summary
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Rockstar🎓
Top SchoolCheng-ping Hsieh is an applied research scientist at NVIDIA specializing in long-context LLMs and speech technologies, with seven years of experience spanning industry and academic research. He combines practical MLOps and deployment experience—shipping TTS systems in NeMo and accelerating CPU inference pipelines at Amazon—with deep research in NLP, speech processing, and parameter-efficient adaptation techniques. A UC San Diego master's student and former NTU researcher, he has developed multi‑speaker TTS, prosody control modules, and adapter-based speaker adaptation while also building production ML services (summarization, duplicate detection, sticker search) at LINE. Beyond technical depth, he brings strong cross-functional leadership from student government roles and large event coordination, reflecting an ability to translate complex research into user-facing systems at scale.
7 years of coding experience
4 years of employment as a software developer
University of California, San DiegoBachelor of Science in Electrical Engineering, Electrical Engineering, Bachelor of Science in Electrical Engineering, Electrical Engineering at National Taiwan UniversityTaipei Municipal Jianguo High School
Github Skills (71)
language-model10
deep-learning10
machine-translation10
multimodal10
nmt10
generative-ai10
conversational-ai10
neural-network10
nlp10
chatbot10
nlp-machine-learning10
speech-synthesis10
speaker-recognition10
natural-language-processing10
speaker-diarization10
Programming languages (3)
Github contributions (5)
hsiehjackson/Emotion-Recognition-AMIGOS_GSR
Jan 2019 - Jan 2019
Contributions:1 commit, 1 branch in 1 day
hsiehjackson/Facial-Beauty-Prediction
Aug 2019 - Jul 2020
Contributions:11 commits, 10 pushes, 1 branch in 11 months
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