First of all, please tell us something about yourself: What hashtags describe you the best?
#Curious, #DataLover, #BridgeBuilder, #LearningJunkie, #PurposeDriven
Please tell us more.
I'm driven by my curiosity and like to question things and dive deep into topics, which means I rarely stop asking questions. Data has always fascinated me, and as a data-lover I like looking for stories and patterns in numbers that others might overlook. In my role as a bridge-builder, I literally connect technology with people, such as doctors, nurses and patients. The "learning-junkie" tag fits because I see every challenge as an invitation to learn something. As for "purpose-driven" that's always been my standard. After all, every data point relates to a person, something I never forget.
Let's talk about your professional activities: What do you do at Lucerne University of Applied Sciences and Arts?
I'm a research associate working on the SmartRehab SNSF project at the university's Institute of Communication and Marketing (IKM). The goal is to improve rehabilitation services for people with spinal cord injuries through AI recommendation systems. I am thus a link between HSLU and the Swiss Paraplegic Centre, connecting technology with everyday clinical practice. In terms of content, I help make AI systems trustworthy and explainable, collect and prepare data, and of course do the relevant research.
What did you do before and why did you join Lucerne University of Applied Sciences and Arts?
I have a background in economics, got my bachelor's degree from the University of Lucerne, and gained my first experience at a marketing agency and a startup, where I quickly realised that working with data fascinates me. Excel eventually became too limiting, so I started the Master's programme in Applied Information and Data Science at HSLU. During my studies, I worked as an assistant and wrote my thesis with my current co-supervisor, who then asked me whether I could imagine joining the team. Doing a PhD was not explicitly part of my plan, but research has always appealed to me, and being given the chance to combine health sciences with AI in an applied context that makes a real difference to others convinced me to take this step.
What is the most exciting part of your job?
The continuous journey of discovery. Every day there is something new to learn, and I enjoy identifying gaps and finding ways to close them. I am particularly fascinated by moments when real insights emerge from unstructured raw data, insights that will ultimately help someone. That's what drives me: seeing data not as an end in itself but as a means to bringing about something meaningful.
Which data science skills are particularly in demand in your job?
At the moment, data engineering and exploratory data analysis get a lot of attention. As the project progresses, however, the entire data science cycle comes into play: from data collection through feature engineering and modelling, all the way to evaluation and visualisation. Something particularly important and often overlooked is the ability to explain complex relationships clearly. In my work, explainability is not only a technical goal but an important communication task involving doctors, nurses and patients.
Do you see yourself more as a techie, an analysis whiz, a creative genius, a management superhero or a brilliant all-rounder?
An all-rounder with an analyst's brain. Working with data, understanding it, questioning it and "getting it to talk" is what really motivates me. At the same time, linking technology with healthcare requires more than just technical skills. I communicate with doctors, work with nurses and have to develop complex models that not only data scientists can understand. So, a healthy dose of all-rounder thinking is definitely an advantage here.
What fascinated you most during your studies in the MSc in Applied Information and Data Science?
Clearly the project work, and specifically the moment when you go through the entire data science cycle, spot patterns and discover what the data is actually telling you. I also found working with others to be especially rewarding: discussing results together, challenging each other, realising that there's often no clear right or wrong. And then ChatGPT came along, which took my curiosity to a new level. Suddenly we could deep-dive even faster, find alternatives and look at problems from additional perspectives. This curiosity continues to carry me to this day.
What are the biggest challenges in your job right now?
Starting a PhD above all means one thing: you are left to your own devices – you read countless papers, go to conferences, gather impressions, and now and then realise that you're out of your league ;-) It takes time to find your niche and understand where you can really make a difference with your research. The first important thing I learned is that the pieces of the puzzle do fall into place eventually, even when at times it may seem that the more I read the less I understand.
What advice would you give to someone who wants to do the same thing as you?
Don't do it for the title. Do it because research is what really fascinates and inspires you. Setbacks are part of the deal: your papers will get rejected, or you study a topic for weeks and then realise that you have the wrong approach. Anyone who can accept that and learn from it will grow. Ambition is important, but resilience may be even more so.
Finally, what new hashtag are you aiming for in future?
#ShapingTheFuture: I want not only to understand how AI works but to actively help shape how it is used responsibly and in a human-centred way. There is enormous potential precisely at the interface of health and technology, and I want to contribute my part there.
We would like to thank Michelle Koch for her dedication and for sharing these valuable insights.
