Newsroom Computational Audiology, March 11
We’re thrilled to share the latest updates from the Computational Audiology Network (CAN), including the launch of our new virtual seminar series, key updates on VCCA2026, and a recap of our impactful session at ARO2026.
CAN Seminars:
The new virtual seminar series in hearing science and computational audiology
We are delighted to invite you to the first CAN Seminar, focusing on Deep Learning for Better Hearing. This virtual event will explore how deep neural networks are revolutionizing speech perception in noisy environments—a major challenge for people with hearing loss.
Speakers:
- Prof. Dr. Stefan Launer, Vice President Audiology and Health Innovation, Sonova AG, Switzerland
- Prof. Dr. Timo Gerkmann, Head of Signal Processing Group, University of Hamburg, Germany
Date and Time:
30 March 2026, 13:00 – 14:30 (Central European Summer Time)
Location:
Virtual (Zoom), the seminar will be recorded and shared afterwards
Registration:
Free attendance, but registration is required via Eventbrite.
Description:
Join us for two expert presentations and a community discussion on the latest advancements in deep learning for hearing technology. This seminar bridges industrial and academic research, offering unique insights into the future of auditory science.The seminar will be chaired by Tobias Goehring, Jhennifer Queiroz Raimundo, and Jan-Willem Wasmann.
Prof. Dr. Stefan Launer, Vice President Audiology and Health Innovation, Sonova AG, Switzerland
Prof. Dr. Timo Gerkmann, Head of Signal Processing Group, University of Hamburg, Germany
VCCA2026
We are proud to introduce the Scientific Committee for VCCA2026 – the 7th Virtual Conference on Computational Audiology. Each member will lead a multidisciplinary thematic session, fostering collaboration across hearing science, clinical research, engineering, and neuroscience.
Submit your abstract
Register via Eventbrite:
A preliminary programme overview, including the structure and indicative timings, is available here:
Conference Themes:
- Day 1: Understanding Hearing – From Perception to Cognition
- Computational Audiology & Digital Hearing Research
- Binaural Hearing & Spatial Sound Perception
- Speech-in-Noise and Auditory Scene Analysis
- Cognition, Listening Effort & Brain Connectivity
- Hidden Hearing Loss and Subclinical Auditory Disorders
- Objective Measures and Biomarkers in Hearing Research
- Day 2: Transforming Hearing Science – From AI to Clinical Impact
- Machine Learning & AI for Hearing Science
- Tele-Audiology and Next-Generation Clinical Tools
- Cochlear Implants: Challenges and Prospects
- Hearing-Aid Innovation and Performance Assessment
- From Lab to Clinic: Ensuring Impact of Computational Hearing Research
- Multisensory and Vestibular Integration
Key Dates
- Abstract submission deadline: 3 May 2026
- Acceptance notification: 17 May 2026
- Conference materials submission deadline: 7 June 2026
- Conference: 25–26 June 2026
We warmly welcome submissions from across the hearing sciences, including computational audiology, clinical audiology, auditory neuroscience, speech perception, machine learning, and assistive technology.
We look forward to welcoming you to VCCA 2026!
If you have any questions, please contact us at:
vcca2026@computationalaudiology.com
With best wishes,
the VCCA 2026 Organising Committee
Dr. Joaquín T. Valderrama, Dr. Maria Amparo Callejón Leblic, Dr. Miriam Isabel Marrufo Pérez
Hearing Science at the Technological Frontier: ARO2026 Recap
At the 49th Annual MidWinter Meeting of the Association for Research in Otolaryngology, CAN members hosted a special session highlighting an important shift in hearing science. Rather than showcasing isolated innovations, the session demonstrated how artificial intelligence, scalable data infrastructures, remote experimentation, and adaptive laboratory systems are converging into a unified research paradigm. Chaired by Dr. Seba Ausili (University of Miami, USA) and co-chaired by Dr. Tobias Goehring (University of Zurich, Switzerland), the overarching message was clear: hearing science is entering a systems era. The session emphasized integration over fragmentation. From remote data collection and standardized formats to AI-driven interpretation, adaptive lab execution, and computational modeling, these components can now function within a connected experimental pipeline. The closing live demonstration crystallized this vision, illustrating how coordinated technologies can transform traditional workflows into scalable, interoperable, and dynamically responsive research systems.
From Data to Dialogue: Intelligent Interpretation in Real Time
Large language models are no longer conceptual curiosities; they are becoming operational tools. Dr. Jessica Monaghan (National Acoustics Laboratories, Australia) explained that how can interpret behavioral data, generate structured summaries, assist in experimental refinement, and suggest individualized follow-up paradigms. In doing so, they create a bridge between raw datasets and actionable research decisions.
From the Sound Booth to the World: Remote Assessment
At the same time, Dr. Tobias Goehring presented on how remote and online testing platforms are expanding the reach of auditory science beyond specialized booths. Scalable, personalized testing enables broader recruitment, longitudinal monitoring, and more ecologically valid data. This shift has implications not only for research efficiency but also for equity and accessibility in hearing care.
The Rise of Interoperable Auditory Data
As datasets grow in size and diversity, standardization becomes essential. Dr. Mareike Buhl (University of Oldenburg, Germany) emphasized structured auditory profiling and harmonized data formats that allow clinical and research pipelines to connect seamlessly. It lays the foundation for cross-site reproducibility, large-scale modeling, and cumulative science in audiology.
Laboratories That Think in Real Time
Modern laboratory infrastructures are becoming flexible, modular, and responsive. Adaptive stimulus control, spatial and multisensory configurations, and real-time modulation allow researchers to move beyond static paradigms. Dr. Seba Ausili illustrated how next-generation smart laboratories enable experiments that adapt dynamically and better approximate ecologically valid listening environments, emulating complex real-world auditory scenes while maintaining experimental precision.
Modeling Human Hearing at Scale
General-purpose deep neural networks are emerging as computational models of auditory behavior. Dr. Fotios Drakopoulos (University College London, UK) demonstrated how the latest advances in large-scale electrophysiology and deep learning can be combined to predict the behavioral performance of individual listeners with and without hearing loss. This modeling approach advances our understanding of inter-individual variability, links peripheral impairment to perceptual outcomes, and supports more predictive, personalized research frameworks that can pave the way for the next generation of sound technologies and hearing aids.
Integration as the Defining Innovation: “Now… All together!”
The defining moment of the session was not any single technology, but their integration. The closing demonstration showed how remote testing, standardized data, language models, adaptive lab systems, and neural networks can operate as a unified experimental pipeline. The panelists showed a transition from fragmented technological advances to cohesive research ecosystems. Tools that once functioned independently can and has to be interoperable components of a modular, scalable framework for hearing science.
The Computational Audiology Network session demonstrated that the tools needed for this transformation are already here. The challenge now is not whether innovation is possible, but how quickly the field is willing to build with it.
The CAN team: Seba, Fotis, Tobias, Mareike and Jessica at ARO
Job Opportunity: Postdoctoral Researcher in the Deep Hearing Lab
The Deep Hearing Lab is seeking a Postdoctoral Researcher to develop computational methods for improving cochlear implant stimulation strategies. This role involves interdisciplinary collaboration across Zurich, Cambridge, Paris, Oldenburg, and Boston, focusing on AI-driven optimization and neural process simulations. The position is based at the University of Zurich and University Hospital Zurich, and offers career development support, mentoring, and networking opportunities.
Application deadline: 31 March 2026
Apply here: Postdoctoral Researcher in the Deep Hearing Lab
Reminder: Academics can share job opportunities on our website for free. Visit Computational Audiology Jobs and email us your advertisement to post your openings.
Up Next
Stay tuned for more details on the upcoming. Computational Audiology Network events. We look forward to your participation!