Andy Harper
About Andy Harper
Andy Harper serves as the Manager and Tech Lead for Audio Machine Learning at Logitech, where he has been instrumental in growing his team and developing relationships with leading universities. He has a background in machine learning and acoustics, with experience at various companies including MUSIC Tribe and Celestion.
Current Role at Logitech
Andy Harper serves as the Manager and Tech Lead for Audio Machine Learning at Logitech, a position he has held since 2022. In this role, he oversees the development and implementation of audio machine learning projects. He has successfully expanded his team of embedded audio ML engineers from three to nine members, enhancing the team's capacity to tackle complex audio challenges. His leadership focuses on fostering innovation and collaboration within the team.
Previous Experience at Logitech
Prior to his current role, Andy Harper worked at Logitech as a Lead Audio Machine Learning Engineer from 2021 to 2022 and as a Senior Audio Machine Learning Engineer from 2020 to 2021. During his tenure, he contributed to various audio machine learning initiatives, leveraging his expertise to advance the company's audio technology offerings.
Experience at MUSIC Tribe
Andy Harper was employed at MUSIC Tribe as a Machine Learning Specialist and Senior Acoustic Engineer from 2018 to 2020. He supervised intern projects in collaboration with EPFL through the CTO office. His role involved applying machine learning techniques to acoustic engineering challenges, contributing to the development of innovative audio solutions.
Educational Background
Andy Harper holds a BSc (Hons) in Physics from Royal Holloway, University of London, which he completed from 2006 to 2009. He furthered his education with an MSc in Sound and Vibration Studies from ISVR - University of Southampton, graduating in 2011. This academic foundation supports his expertise in audio technology and machine learning applications.
Collaborations and Projects
Andy Harper has collaborated with notable organizations such as the BBC and Google on the EPSRC-funded Machine Learning Challenge 'Cadenza,' aimed at assisting individuals with hearing impairments. He has also engaged in the design and oversight of tech architecture for audio machine learning projects, contributing to the development of multiple cloud-based ML pipelines.