Holger Bovbjerg is a PhD fellow in AI and Sound at Aalborg University with eight years’ experience applying machine learning to signal processing for hearing assistive devices. His research focuses on self-supervised learning for multichannel speech and embedded hearing systems, building on a master’s thesis in self-supervised keyword spotting and a Fulbright-supported visit to CMU’s WavLab. He combines hands-on engineering—from TensorFlow model pipelines and CI/CD work at CERN to prototyping for hearing aids—with strong academic training in signal processing and acoustics. Colleagues describe him as tenacious and team-oriented, qualities he attributes to long-term involvement in football and student mentoring. Holger’s work sits at the intersection of practical deployment constraints and cutting-edge ML methods, aiming to bring robust speech models into real-time, resource-limited devices.
8 years of coding experience
Master of Science - MS, Signal processing and acoustics with specialization in Signal Processing and Computing, Master of Science - MS, Signal processing and acoustics with specialization in Signal Processing and Computing at Aalborg University
High School (STX), Math, Physics and Chemistry, High School (STX), Math, Physics and Chemistry at Aalborghus Gymnasium
BSc, Electronics and IT, BSc, Electronics and IT at Aalborg Universitet
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Holger Bovbjerg - PhD Fellow - AI And Sound at Aalborg University