Personalization of User Needs

1st June @ 15.00 - 16.30

Smartphone-connected hearing aids make it possible to collect real-world data about the preferences and context of users. This enables both gaining a deeper understanding of users’ behavior, as well as developing a better in-situ and context-aware personalization. We will hear from two researchers working within the hearing aid industry  – Alessandro Pasta, Demant / DTU, and Bert de Vries, Professor at TU Eindhoven and GN Resound – about this important subject.

Form: webinar

Date: 1st June 2022

Time: 15.00 – 16.30

Place: Online via Zoom

Price: free

Language: English

If you have questions about signing up, please contact Murielle De Smedt,

Participant profile:

  • hearing aids
  • consumer audio or medical products
You will meet:



Clustering Users Based on Hearing Aid Use: An Exploratory Analysis of Real-World Data

While the assessment of hearing aid use has traditionally relied on subjective self-reported measures, smartphone-connected hearing aids enable objective data logging from a large number of users. This study aims to explore patterns of hearing aid use throughout the day and assess whether clusters of users with similar use patterns can be identified. We did so by analyzing objective hearing aid use data logged from 15,905 real-world users over a 4-month period.

Alessandro Pasta, Senior Data Scientist, PhD, Demant

Alessandro Pasta is a Ph.D. student at the Technical University of Denmark (DTU) in the area of Computer Science and works as Senior Data Scientist at Demant A/S. He holds a M.Sc. degree in Economics and Management of Innovation and Technology from Bocconi University. His research aims to personalize hearing aid technologies by deepening the understanding of hearing aid users’ preferences and behavior. His research leverages data collected in real-world environments through smartphone-connected hearing aids.

A Bayesian Approach to Hearing Aid Personalization

In this presentation we describe a Bayesian intelligent agent that helps hearing aids patients to solve hearing problems on-the-spot under situated conditions. The agent is based on the Free Energy Principle, which is a neuroscientific theory for how brains compute and make decisions.  

Bert de Vries received MSc (1986) and PhD (1991) degrees in Electrical Engineering from Eindhoven University of Technology (TU/e) and the University of Florida, respectively. Since April 1999 he has been employed in the hearing aids industry (currently at GN Hearing), both in research and managerial roles. Since January 2012 he is also a full professor at the Signal Processing Systems Group at TU/e, where he teaches a course on Bayesian machine learning to graduate electrical engineering students. At TU/e he directs the BIASlab research team of graduate students with whom he conducts research on transferring a Bayesian brain theory (the Free Energy Principle) to practical engineering applications. 

Niels Pontoppidan will join us as a moderator for this event.

He manages research for Oticon at Eriksholm Research Center. His research areas combine AI for finding the optimal individual settings for varying intents and sound scenes as well as enhancing voices processing with AI. He has a PhD from DTU Compute in 2005 and started on voice separation with machine learning for the master’s project in 2001.

When you participate in this event, your time will be used as co-financing for the Innovation Power Project, which is funded by the Danish Business Promotion Board and the Danish Agency for Education and Research at a standard rate. Read more about Innovationskraft  HERE.

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