معرفی
Jesper Jensen is a Professor at the Department of Electronic Systems, part of The Technical Faculty of IT and Design at Aalborg University. His research focuses on acoustic signal processing, machine learning, and speech enhancement, with particular expertise in applications like hearing aids, noise reduction algorithms, and deep learning architectures for audio systems. He serves as a project supervisor at institutions including Oticon A/S since 2007, and co-leads the CASPR (Centre for Acoustic Signal Processing Research) center.
Key research interests include multichannel signal processing, robust speech enhancement in reverberant environments, and adaptive filtering techniques. His work integrates Bayesian methods, deep neural networks (DNNs), and sparse modeling to address challenges in audio localization, speech presence probability estimation, and sound zone control systems.
- Notable Achievements:
- Recipient of the prestigious 'Stor international pris' award in 2017
- Over 135 publications in journals like IEEE Signal Processing Letters and conference proceedings
- Active collaborations with industry partners such as Oticon A/S
His research outputs emphasize practical applications, including voice control systems for hearing aids, binaural speech enhancement in noisy environments, and acoustic reflector localization for robotics. Recent work explores transformer networks and learning-based frameworks for real-time audio processing.
