Anna Shvets
Principal Investigator Of AHRC AAI Grant
Nottingham, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolAnna Shvets is an interdisciplinary researcher and assistant professor specializing in interactive music technology and generative AI, currently leading multiple AHRC and EPSRC-funded projects at the University of Nottingham. With a PhD in computational musicology and eight years of professional experience, she blends conservatory-level composition and piano training with hands-on engineering as a certified deep learning engineer and full-stack developer. Her work pioneers Music XR—introducing volumetric music composition—and advances conditional generative models (conditional GANs and spiking convLSTMs) for low-power, creative audio applications. An award-winning VR artist and active open-source contributor, she has helped improve bias-detection filters in the widely used NL-Augmenter repository. She regularly speaks at major industry and academic venues and serves as an editor and long-time reviewer for digital art conferences, combining aesthetic sensibility with rigorous technical evaluation. Beyond research, she designs outreach and wellbeing programs that bring AI-powered immersive music experiences to diverse communities.
8 years of coding experience
7 years of employment as a software developer
Generative Adversarial Networks (GANs), Generative Adversarial Networks (GANs) at CourseraNanodegree Intel Edge AI for IoT Developers, Nanodegree Intel Edge AI for IoT Developers at UdacityDoctor of Philosophy (PhD) Computational musicology, Doctor of Philosophy (PhD) Computational musicology at Uniwersytet Marii Curie-Skłodowskiej w LublinieLicentiate degree Church Organist, Licentiate degree Church Organist at Institute of Sacral Music in PrzemyslLicentiate degree Music Theory and Composition, Licentiate degree Music Theory and Composition at Ukrainian National Tchaikovsky Academy of Music
Ukrainian, Polish, English, French
Github Skills (8)
filtering10
nlp10
filter10
python10
natural-language-processing10
computer-engineering9
machine-learning9
f7
Programming languages (4)
Github contributions (5)
GEM-benchmark/NL-Augmenter
Jul 2021 - Jul 2022
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Role in this project:
Back-end Developer
Back-end DeveloperContributions:28 reviews, 60 commits, 9 PRs in 1 year
Contributions summary:Anna primarily contributed to the development of bias detection filters within the NL-Augmenter project. Their work involved creating and refining filters to identify gender bias and universal bias in natural language text, with each filter designed to flag sentences based on the presence of specific keywords or patterns. The user added new filters, modified existing ones, and included features such as percentage calculations, language support and error handling to improve the functionality and robustness of the project's bias detection capabilities.
nlpinformation-theorysentencedeep-learningmachine-learning
asnota/NL-Augmenter
Jul 2021 - Jul 2022
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Contributions:2 PRs, 63 pushes, 11 branches in 1 year
nlpdeep-learningmachine-learningnatural-languagetransformations
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