Anastasia Kuznetsova is a postdoctoral researcher and applied scientist with nine years of experience at the intersection of computational linguistics, speech processing, and frontend development. She holds a PhD in Computer Science and Computational Linguistics from Indiana University and has worked on voice conversion and anonymization for an IARPA-funded project at the University of Rochester. Her background spans academia and industry with internships and roles at Amazon, Google, Rev, and Coqui, where she contributed to foundational models for multi-channel audio and deployed machine learning systems. As an instructor she taught graduate courses on deep learning systems and ML for signal processing, reflecting a commitment to both research and practical engineering. Colleagues note she pairs rigorous research with product-minded implementation—an unusual blend that makes her effective at translating cutting-edge audio research into usable tools.
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