Tao Zhang
Sr. Manager Of Applied Science at IEEE
Eden Prairie, Minnesota, United States
Summary
🤩
Rockstar🎓
Top SchoolTao Zhang is a senior applied science leader with over two decades of experience in signal processing, machine learning, and ultra low-power embedded development for hearing and wearable devices, currently leading applied science at Amazon. He combines rigorous technical expertise—anchored by a Ph.D.—with hands-on algorithm development in audio, acoustics, psychoacoustics and keyword spotting, and has progressed from research scientist to director-level roles at Starkey before moving into industry leadership. Tao is an IEEE SPS Distinguished Industry Speaker, reflecting his ability to translate deep research into practical product impact and industry thought leadership. He also contributes to open-source speech tooling, e.g., preparing dataset infrastructure for the widely used SpeechBrain toolkit, showing a pragmatic focus on reproducible ML workflows. Based in Eden Prairie, Minnesota, he is known for an open-minded, can-do management style that balances creativity with engineering discipline to ship real-time, resource-constrained audio solutions.
9 years of coding experience
19 years of employment as a software developer
B.S., B.S. at Nanjing UniversityM.S., M.S. at Peking UniversityPh.D., Ph.D. at The Ohio State University
Chinese, English
Github Skills (11)
data-preprocessing10
pytorch10
dataprep10
speech-processing10
speechbrain10
python10
audio-processing9
speech-recognition9
asr7
deeplearning-ai7
deep-learning7
Programming languages (1)
Github contributions (5)
speechbrain/speechbrain
May 2020 - Nov 2021
A PyTorch-based Speech Toolkit
Role in this project:
Back-end Developer
Back-end DeveloperContributions:52 commits, 2 PRs, 2 pushes in 1 year 6 months
Contributions summary:Tao's primary contribution involved preparing data for the Voicebank dataset within the SpeechBrain toolkit. This included writing a Python script to create CSV files that organize and index the dataset's audio files, along with their corresponding clean audio files, for training and testing. The script downloads the Voicebank dataset from the provided URL. The user's work directly supports the development of speech processing models and provides the necessary data infrastructure.
voice-recognitionasrspeech-recognitionspeech-separationspeaker-verification
JasonSWFu/MetricGAN
May 2019 - Apr 2021
Contributions:33 commits, 32 pushes, 1 branch in 1 year 11 months
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