Deepak Baby is a Senior Data Scientist with a PhD from KU Leuven and over a decade of experience applying statistical signal processing, sparse representations, and neural models to speech enhancement and robust ASR. He has transitioned research innovations into product-scale work as an Applied Scientist on Amazon Alexa’s AGI team, leading continuous learning and fast incremental updates for speech recognition and multimodal LLM integration. His academic work produced novel exemplar-based denoising/dereverberation methods and biologically inspired cochlear approximations that enabled real-time, hearing-aid–oriented neural models published in high-impact venues. Now based in Leuven and working in banking analytics, he brings a rare combination of deep theoretic expertise and production ML experience, particularly in bridging auditory neuroscience, GAN-based waveform enhancement, and scalable ASR systems.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD) Non-negative Sparse Representations for Speech Enhancement and Recognition, Doctor of Philosophy (PhD) Non-negative Sparse Representations for Speech Enhancement and Recognition at KU Leuven
Indian Institute of Technology Bombay
Bachelor of Technology (BTech) Electronics and Communication Engineering, Bachelor of Technology (BTech) Electronics and Communication Engineering at College of Engineering Trivandrum
Contributions:6 commits, 5 pushes, 1 branch in 11 months
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