Scott Wisdom
Staff Research Scientist at Google DeepMind
Greater Boston United States
Summary
👤
Senior🎓
Top SchoolScott Wisdom is a Staff Research Scientist at Google DeepMind with 11 years of experience bridging academia and industry in machine learning, deep learning, and statistical signal processing for challenging real-world signals like speech and audio. He earned a PhD in Electrical Engineering from the University of Washington, where his dissertation developed methods that fuse statistical models and deep networks to yield principled initializations, improved training, and interpretability. Scott’s work spans research roles at Google, Affectiva, and internships at MERL and Microsoft Research, plus early engineering on DSP, firmware, and FPGA systems, giving him a rare mix of theoretical rigor and hands-on systems experience. Based in Greater Boston, he focuses on modeling, separation, classification, and enhancement in noisy or reverberant environments and is known for translating principled signal-processing insights into practical deep-learning architectures.
11 years of coding experience
14 years of employment as a software developer
PhD Electrical Engineering, PhD Electrical Engineering at University of WashingtonBachelor of Arts (BA) English Literature, Bachelor of Arts (BA) English Literature at University of Colorado Boulder
Github Skills (11)
nmf10
recurrent10
gmm10
factorization9
speech9
ctc9
matrix-factorization9
machine-learning8
ai8
google8
matrix8
Programming languages (2)
Github contributions (5)
stwisdom/dr-nmf
Apr 2017 - May 2019
Implementation of deep recurrent nonnegative matrix factorization (DR-NMF) for speech separation
Contributions:23 commits, 1 PR, 24 pushes in 2 years
factorizationctcgmmmatrix-factorizationspeech-separation
google-research/sound-separation
Mar 2020 - Oct 2024
Contributions:23 pushes, 1 branch in 4 years 7 months
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