I will build high accuracy audio classification and ml models

Audio data is messy. I turn complex soundscapes into highly accurate predictive models.

If you are dealing with raw audio data for environmental monitoring, wildlife conservation, or complex audio classification, standard off-the-shelf models won't cut it. You need a customized architecture that understands how to process soundscapes properly.

I specialize in bioacoustic machine learning and advanced audio classification. I don't just run data through standard models; I engineer the data from the ground up, converting raw audio files into clean mel-spectrograms, and building highly tuned ensemble models that achieve competitive accuracy.

Whether you need to identify specific bird calls in noisy environments or classify distinct non-human soundscapes, I have the proven technical background to deliver. I have successfully architected models that achieve 0.930+ accuracy scores in competitive, global classification environments.

• Expert Data Engineering: Flawless conversion of .ogg, .wav, and raw audio into optimized mel-spectrograms using librosa and custom pipelines.
• Advanced Architectures: Custom implementation of EfficientNet, Perch, ProtoSSM, and other