Cheng-Ping Hsieh in

Cheng-Ping Hsieh

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NeMo (LLM Long Context) - Applied Research Scientist at NVIDIA
📍 United States

Cheng-Ping Hsieh is an Applied Research Scientist at NVIDIA on the NeMo team, specializing in long-context large language models. A graduate of UC San Diego and National Taiwan University, his expertise spans natural language processing, speech synthesis, and MLOps, with previous experience at Amazon and LINE.

He co-authored "YourTTS, " an influential research paper on zero-shot multi-speaker Text-to-Speech, showcasing his impact on advanced speech synthesis.

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Experience
4 Years
Current Role
NeMo (LLM Long Context) - Applied Research Scientist
Location
United States
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Priorities

Topics Cheng-Ping cares about

Speech Synthesis
Developed a multi-speaker Text-to-Speech (TTS) framework for NVIDIA's NeMo and co-authored research papers on zero-shot TTS and speaker adaptation.
Large Language Models
His current role at NVIDIA involves research and application of LLMs, specifically focusing on extending their context length within the NeMo framework.
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Career

Work history

2-2023
NeMo (LLM Long Context) - Applied Research Scientist
NVIDIA
9-2021 - 12-2022
Graduate Student Researcher
UC San Diego
6-2022 - 9-2022
NeMo (TTS) - Applied Research Scientist
NVIDIA
5-2021 - 8-2021
D2AS - Applied Scientist Intern
Amazon
9-2020 - 5-2021
Machine Learning Engineer
LINE Taiwan Limited
In the press

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Education
9-2021 - 12-2022
Master of Science - MS
UC San Diego
2015 - 2019
Bachelor of Science in Electrical Engineering
National Taiwan University
Social presence
in
Behavioral profile

DISC profile (public)

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