How can researchers make the design of medical devices more inclusive? Measuring characteristics of patients correctly can make all the different, e.g. in surgery, because it improves effectiveness of outcomes.

In this episode of our podcast series on Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM), Prof. Dr. Domenico Della Volpe from Geneva University shares insights on his research with the host, Dr. Claudia Werker from Delft University of Technology. Both have been working on the @ATTRACT project: Domenico on the engineering side and Claudia on the business side of the project.

Dominico Della Volpe is a particle physicist with a keen interest in Radio-Guided Surgery (RGS) in nuclear medicine. In this podcast, he shares his journey developing a new medical device, POSICS-2, for tumor treatment through RGS, highlighting how the diverse needs of individuals influence the final design of such devices. Domenico stresses both the vital role of interdisciplinary collaboration and the need to address unconscious biases in research to make Inclusive Research and Innovation in STEM happen.

Learn more about the development of POSICS-2 tumour treatment medical device within the ATTRACT project:

https://phase2.attract-eu.com/projects/posics-2/

We are halfway through our first season and thought it was time to introduce the host of the podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM)! In this special mini-episode, research assistant Tian Qing Yen interviews the host of the series Dr. Claudia Werker from Delft University of Technology. Claudia explains how she became interested in IRI in STEM and shares some of the challenges and opportunities she has faced in both doing research on and promoting IRI in STEM.

Speech recognition and processing tools are everywhere – from speech-to-text transcription, to voice commands on your phone, to filtering background noise in video calls. However, many automatic speech recognition systems do not perform as well with diverse speakers, i.e. people with an accent, with a speech impediment, or even young or old speakers. Adjusting this technology to recognize different ways of speaking has the potential to make these systems and the tools that depend on them more accessible and inclusive. What challenges and opportunities are there for developing and using more inclusive speech recognition and processing?

In this episode of our podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics, Dr. Claudia Werker from Delft University of Technology talks to her colleague Dr. Odette Scharenborg from the same university. Dr. Scharenborg’s research looks at how to improve speech recognition systems for non-standard speakers. She explains that while acquiring and processing the varied data she needs for her work is challenging, it has also led to opportunities to connect with diverse speakers, to advocate for them, and to help them practically navigate using speech recognition tools.

Learn more about Dr. Scharenborg's research:

• Feng, S., Halpern, B., Kudina, O., & Scharenborg, O. Towards inclusive automatic speech recognition (2024)
• Feng, S., Kudina, O., Halpern, B., & Scharenborg, O. Quantifying bias in automatic speech recognition (2021)