23 April 2024

Hanne Biesmans, PhD student at Linköping University, has been selected for the annual prestigious list "Forbes Under 30 Europe Class Of 2024" in the category Science and health care.

Headshot of a young female reseacher by a microscope. Photographer: Thor Balkhed

Cultivated electrodes – one of the biggest breakthroughs of the year

Hanne Biesmans and her team are developing a new generation of injectable electrodes that can self-assemble inside living tissues. This technology could potentially make certain neurological treatments safer, more cost-effective and accessible. Biesmans is co-first author of an article published in Science last year about the initial project results.

How the assessment of the participants on the list is made

Judges in the category Science and health care 2024 were Josef Aschbacher, Johanna Bergman, Deepali Nangia and Stefan Woxström.

To compile the ninth annual list, Forbes writers and editors combed through thousands of online submissions, as well as used industry sources and listed alumni for recommendations. The candidates were evaluated by Forbes staff and a panel of independent expert judges (including billionaire and denim powerhouse Diesel owner Renzo Rosso, actor Simona Tabasco and Olympic gold medallist Mo Farah) on a variety of factors, including funding, revenue, social impact, scale, ingenuity and potential. All selected must be 29 years of age or younger on April 9, 2024.

Read more about Forbes 30 Under 30 Europe 2024 here.

Latest news from LiU

A man standing in a lab.

Prestigious chemistry award to Simone Fabiano

This year’s Göran Gustafsson Prize in Chemistry is awarded to LiU Professor Simone Fabiano. His research focuses on organic semiconductors and how so‑called doping can improve conductivity and yield new properties.

En person i labbrock som håller i en flaska.

AI provides a more precise time of death

Artificial intelligence can be used to provide a more precise time of death, which can be crucial in e.g. murder investigations. The AI model is trained on so-called metabolites in thousands of blood samples from real deaths.

A man working on a machine in a lab.

AI-boosted electronic nose detects ovarian cancer

Using machine learning, an electronic nose can “smell” early signs of ovarian cancer in the blood. The method is precise and, according to the LiU researchers behind the study, it could eventually be used to find many different cancers.

Explaining the research

Electrodes grown in living tissue

Hanne Biesmans, PhD student at the Laboratory of Organic Electronics, explains how they managed to grow soft electrodes in living tissue.