Aditya TB is a Staff Machine Learning Engineer with 9 years of multidisciplinary experience bridging music technology, audio DSP, and deep learning, currently focused on audio deepfake detection and protection at Resemble AI. Trained at McGill (Music Technology) and with a background in ECE, he combines computational acoustics, physical modeling, and haptic-feedback research with practical skills in audio restoration, field recording, and production. He has published work in haptics for music and built tooling to analyze reverberation artefacts, reflecting a strong research-to-production trajectory. A former founder of an audio agency and seasoned sound designer, he pairs product-minded engineering with hands-on electronics and signal processing expertise. Outside engineering, he brings 14+ years of Carnatic vocal training and orchestral performance experience, a musical depth that informs his approach to auditory inference and perceptual ML.
9 years of coding experience
9 years of employment as a software developer
Diploma Audio Engineering, Diploma Audio Engineering at SAE Institute - Chennai
Bachelor of Technology (B.Tech.) Electrical Electronics and Communications Engineering, Bachelor of Technology (B.Tech.) Electrical Electronics and Communications Engineering at Guru Nanak Engineering College
Bachelor of Science (Hons.) Audio Engineering, Bachelor of Science (Hons.) Audio Engineering at SAE Institute London
Master of Arts (M.A.) Music Technology, Master of Arts (M.A.) Music Technology at McGill University
Implements python programs to train and test a Recurrent Neural Network with Tensorflow
Contributions:13 commits, 13 pushes, 2 branches in 6 months
pythonrecurrent-neural-networkstensorflow
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