Shaping the future of science through AI at Helmholtz: Meet Dr. Sonja Hänzelmann

To celebrate International Girls in ICT Day, we are putting the spotlight on one of our Helmholtz AI Associates who are driving innovation in AI across diverse research fields. Today, we have the pleasure of introducing Dr. Sonja Hänzelmann. She leads the Data Science group at the Alfred Wegener Institute (AWI) for Polar and Marine Research in Bremerhaven, where she develops data‑science and AI approaches to analyze big, complex, and multimodal datasets, advancing our understanding of ecosystem and biodiversity change in polar and marine systems.

What is your current research focused on?

Let me start by explaining what we work on directly. For example, we develop AI models that analyze underwater acoustic recordings to explore whale communication, methods that reveal what is inside an ice core, and approaches that work with molecular and genetic data from Arctic mammals, multi‑omics and environmental DNA, or three‑dimensional segmentation of marine organisms.

From there, it becomes clear why the AWI is such a strong environment for this kind of research. We work in a highly collaborative setting, closely connected with researchers across disciplines and with colleagues who ensure that data collected in the field – including vegetation, ice, water, and soil – can be processed, analyzed, and preserved for the future. The institute offers an exceptional range of long‑term and multimodal observations, making it a uniquely rich place for data‑driven science – the kind of environment that sparks joy in anyone who loves turning complex data into insight.

Within this context, our research focuses on data science, bioinformatics, and AI to address questions in polar and marine science. A key part of our work is developing AI methods that help us understand environmental systems and uncover patterns in the large, diverse datasets generated by modern field research.

Also, teaching is an important part of what we do, and it’s something we genuinely enjoy. We offer a variety of courses on machine learning and AI, including a recent addition where participants learn Python by programming small modular robots built from click‑together building blocks.

What inspired you to pursue a career in science/AI? Was there a key moment, person, or experience that motivated you?

It all started when my parents finally gave in and bought me a computer. The first thing I did was take it apart and put it back together – I always wanted to understand how things work. That curiosity never stopped, whether I was trying to understand diseases on a molecular level, what’s happening inside an ice core, what the seal ate or what whales are chatting about in their acoustic recordings. Computers let us look into worlds we can’t see directly.

I love programming, algorithms, and pattern recognition, and I’m still amazed by what large language models can achieve. What motivates me most is using these tools to solve real‑world problems. For many years I worked in a clinical environment, applying data science to improve patient care by analyzing molecular data and developing methods that support medical decisions. Now I bring those skills to Earth and environmental research. Working on biodiversity, climate‑related change, and the health of our planet feels like a natural extension of that original curiosity.

What advice would you give to girls/women hesitant to study/work in AI?

I would tell girls, women and generally anyone who is hesitant about studying or working in AI to be brave and give themselves permission to try. You don’t need to know everything at the beginning - nobody does. Start with a course, talk to others who are learning, and reach out to group leaders or professors whose work genuinely interests you. Most people are far more approachable than you think. Internships are also a great way to get hands‑on experience, test the waters, and see whether the field feels right for you.

How did you learn about Helmholtz AI? Is Helmholtz AI influencing your work in any way? We saw you at HAICON25 in June last year – what were your impressions and what did you take back from there?

Helmholtz offers an incredible network, and some key people who naturally bring others together. These connectors are invaluable because they have a great overview of who is doing what and who should be talking to whom. The Helmholtz AI groups, each with their own focus, are fantastic. The HAICON captures the spirit of Helmholtz for me: open, collaborative, and full of people who want to help each other move science forward.

Any final words?

Thank you for your amazing work and bringing AI researchers together.