I have a PhD in speech recognition and 20+ years of experience in the research and development of machine learning for perceptual AI, with a significant number of publications in the domain, including 19 patents (more detail in my CV). Although my expertise has primarily applied to R&D in computer hearing, which includes automatic speech and speaker recognition, speech synthesis, music processing and generic environmental sound recognition, the processes involved in machine learning are similar for many other application domains such as computer vision, drug discovery, data mining or fintech.
Starting to develop sound recognition products at Audio Analytic back in 2012 was a significantly pioneering endeavour: sound events recognition was in its infancy, it was standing 50 years behind speech and music recognition, and there was only a handful of academic publications on the topic. In 2022, the sound recognition technology whose development I led at Audio Analytic was world leading, and the company was acquired by Meta. Since then, I have built and led three more applied R&D teams to deliver innovative AI/ML products: at Music Tribe, a multimillion dollars audio equipment company, at Canopy, a startup backed by Ford, and at Green Light Audio, my own startup.
For a summary of my achievements in AI and machine learning, please read my CV or connect with me on LinkedIn. I look forward to helping you to develop your own AI/ML products!
The kind of books I read (and write) about AI/ML include:
If you have any questions about building a product or a digital transformation strategy based on AI and machine learning, please contact me.