This summer, I took on something completely new: clustering algorithms. I had never worked with them before, but during a six-week internship at the Swiss Federal Institute for Snow and Avalanche Research (SLF), I had the chance to dive in and learn. I was part of the Hydrology and Climate Impacts in Mountain Regions (HYCLIMM) group, which focuses on understanding how hydrological extremes and climate interact in mountainous regions.

The topic of my internship built on something I knew a bit about – droughts in rivers – which I had explored during my bachelor’s thesis. But this time, the goal was to go a step further: develop a method to group drought events from the past 40 years based on how they were formed – their hydrometeorological generation processes. These can be a precipitation, storage or snowmelt deficit, high temperatures and increased evapotranspiration, or a combination thereof. After creating the clusters, I would then explore them in more detail: when and where do they happen? How long do they last? How severe are they? And how have they changed over time?

The internship took place in Davos, and I was able to stay there the whole time. That gave me the chance to get to know the team and get a better feel for how they work. It also meant being surrounded by mountains, which made for some great weekend hikes and quiet evening bike rides.

When I arrived, my supervisor Giulia Bruno welcomed me warmly and helped me settle in. The team was kind and open, and some routines – like regular lunches together or afternoon coffee and cake – helped me feel included. I appreciated these small things, and they helped me feel at home quickly.

One of the trickiest parts of my project was the explorative nature of it. There wasn’t a clear roadmap to follow. The first few weeks were all about figuring out what kind of data the clustering algorithm needed to do a good job. As I soon realized, a clustering algorithm is only as good as the data you give it. So, I spent a lot of time selecting and preparing data – trying to feed the algorithm with the “right food,” as I liked to think of it.

What helped was being able to talk things through with the team. They took time to discuss my questions and offered new perspectives. Slowly, things started to make more sense. The clusters began to show meaningful patterns from a process-oriented perspective, and I started asking more focused questions:

• What processes lead to certain clusters?
• Are some more common in specific areas or seasons?
• Has the frequency or severity of these clusters changed over time?

Getting to that point felt rewarding, especially after the initial uncertainties. It also made me more comfortable with the idea that exploration – and sometimes getting stuck – is part of the process.

Beyond the technical skills – like learning how to use clustering methods and improving my programming – this internship also taught me something more personal: how to deal with frustration. Some days were tough, especially when things didn’t work as expected. But over time, I learned to be patient and to trust the process. By the end of the internship, I felt a bit sad to leave. The team had been so welcoming, and I had learned much in such a short time. But I was also proud of what I had achieved. The work I did opened up some follow-up questions, and maybe I’ll get the chance to explore those further, possibly in a master’s thesis.

In January, I packed my bags and flew to Pasadena, California, to start a six-month adventure at NASA’s Jet Propulsion Laboratory. I joined the team working on a future Mars rotorcraft, contributing to a project aimed at pushing the boundaries set by Ingenuity, the pioneering Mars helicopter. This marked the start of an unforgettable chapter, both as an engineer and as a person.

Life at JPL

Life at JPL was unlike anywhere else I’ve worked before. On any given day, you might walk past engineers testing new rover prototypes in the courtyard or catch a glimpse of hardware being readied for launch in the clean rooms. I even got to meet the astronauts from the Artemis crew when they dropped by to visit! All of this felt extraordinary at first, but gradually became part of everyday life. I was part of the software team developing algorithms for an Earth-based demonstrator drone, which serves as a testbed for technologies that could one day guide a future Mars rotorcraft. My main focus was on the autonomy side: designing and refining the software that allows the drone to plan missions, execute waypoint navigation, and make real-time decisions during flight. This is critical, since a drone on Mars cannot be controlled in real time due to communication delays among other things. I also contributed to perception algorithms that detect safe landing sites in rough terrain which is a crucial capability for future planetary flying vehicles. Beyond coding, a big part of the work was integrating and testing everything on real hardware, ensuring the algorithms performed just as well in the lab and outdoors as they did in simulation. Beyond developing algorithms, a big part of the experience was bringing them to life through real drone tests. Our lab had an indoor drone testing room where we could fly whenever needed, and the campus also featured an outdoor drone yard which is essentially a large netted area designed specially for safe flight testing. Supervisors and senior engineers, many of whom had actually worked on Ingenuity itself, stopped by regularly to give guidance and feedback. It was a great environment to learn and develop in, and it was extremely motivating and inspiring.

Testing in the Desert

A particularly memorable part of the internship was a field trip to Death Valley National Park, where our team tested our drones in Mars-like terrain. The goal was to evaluate how well our algorithms handled challenging, unstructured environments which is a valuable step before moving to more advanced trials. The setting, with its dry valleys and rugged rock formations, offered a striking reminder of what exploration on another planet might feel like and the challenges it posed for our perception algorithms. It was demanding work under the sun, but a great opportunity to see our software perform outside the lab. Being out there also made me realize how, while small errors are part of testing on Earth, a similar mistake millions of kilometers away on Mars could mean the end of an entire mission. This makes Ingenuity’s success even more impressive.

Beyond the Lab

Of course, California itself was a whole other adventure. Pasadena quickly became home, even if finding a place to live wasn’t easy when wildfires swept through Los Angeles in January. Daily life was quite different to Switzerland with the car-centric culture, the long distances, and the contrasts of city life. Luckily, it was easy to settle in thanks to the people I met, especially the other interns and students from Caltech in the neighborhood. Together, we filled our weekends with road trips and new experiences: hiking through Joshua Tree, Zion, and Sequoia National Parks; catching sunsets and learning to surf in Malibu, sometimes accompanied by dolphins; exploring San Diego and San Francisco; and even flying to Hawaii. Standing on a surfboard in the middle of the Pacific Ocean, surrounded by turtles, is a memory that will stay with me forever.

Reflections

Looking back, my time at JPL was as much about algorithms and drones as it was about people and places. I met brilliant engineers, many of whom had shaped historic missions, and shared adventures with interns from around the world. I learned that true engineering isn’t about complex solutions, but about making things simple, reliable and robust, especially when they need to work flawlessly millions of kilometers away. Most importantly, I left California hungry for more. More travel, more exploration, and more opportunities to work at the frontier of robotics and autonomy. Whether I continue in industry or one day pursue a PhD, one thing is clear: this internship confirmed that I love the blend of research, teamwork and experimentation that pushes technology and robotics forward.

Closing Thought

Back in Zurich, I’m grateful for how much this experience broadened my perspective: on technology and science, teamwork, and what it means to explore. The mindset I took from JPL stays with me every day, pushing me to keep learning, improving, and reaching further, not only in robotics, but also personally.

Almost a year ago, I stumbled upon an Instagram post from ETH Zurich about an internship offer for the United Nations Office in Bangkok, more precisely at UNDRR (Disaster Risk Reduction). The 21-year-old, applied Maths master’s student I was at the time, with close to no professional experience, did not think for a minute I had a chance. For some reason I decided to I read the offer and noticed met all the requirements, so I gave it a shot.

I applied internally with the ETH Studios, passed this first screen, then with the UN, got the interview, did the interview, got the position, each step being a complete surprise for me and I still was a bit baffled (and jet-lagged) on my first day in office in September. Everything was new (and a bit scary) to me and the onboarding process was a lot to assimilate.

I would describe this internship as a double way learning and teaching experience: I learned from my supervisors and my team (the Tech & Design team of UNDRR) how a big international agency works, and what current technologies are used in disaster mitigation. In turn, I got to teach them a bit about I learned at ETH: neural networks, LLMs, reinforcement learning… and how these tools can be used in the organisation.

As I was the first ever data and AI intern, I had to build from scratch with minimal resources and no pre-existing workflows. We figured out a lot of things on the go. The arrival of two other new interns at the same position as me, one of whom is also an ETH student, helped to speed up our work.

I primarily worked on two projects: a machine learning based catastrophic model for fragility assessment during seismic events, which I did alone, and a RAG chatbot based on UNDRR, with 3 other people. We were able to deliver working Proof Of Concepts for both, which was a big success given our modest beginnings. I was also the first presenter of a series of webinars about AI related topics, which are still delivered weekly to the entire UNDRR staff to this day. 

This goes in hands with what I would consider as my biggest accomplishment during this internship: planting the seeds of a proper machine and deep learning service at UNDRR (which was the vision our team’s boss had in mind when creating the internship offers). By the end of my six months, the proof of concept opened up opportunities for potential partnerships and funding to continue the work. A new ETH student is also starting her internship right when I finish and I personally see a real potential in a closer ETH/UNDRR partnership.

On a personal level, those past 6 months were an amazing adventure, full of new people from all over the world and travels around Thailand and Asia in general. Bangkok ended up feeling like home and coming back to Switzerland and its 9 million people (half of the population of metropolitan Bangkok) will certainly be quite the change; that and the price of groceries!

It feels like I took off for BKK airport only two weeks ago but in the meantime, the person I am now is fundamentally different from the student who arrived a bit late to work with his brand-new suit in September. I guess this is how growing up feels like.

ETH Studios

ETH Studios are global innovation outposts where ETH students tackle real-world challenges alongside companies, researchers, and startups. Whether in New York, Heilbronn, Davos, or at the experimental StudioX, students gain entrepreneurial and interdisciplinary experience while contributing to sustainable and tech-driven solutions.

Contact eth-studios@ethz.ch if you are interested in more information on and about the ETH Studios.

We are four students with backgrounds in Chemical, Computer & Electrical Engineering as well as Computer Science, and we’d love to share our unforgettable internship experience in Japan. Through a collaboration between Marui Group in Nakano, Tokyo and ETH Studios, we were given the opportunity to explore the intersection of culture, sustainability, and design innovation.

Our journey began on June 27th, 2025, when we arrived at the Marui headquarters, jet-lagged but excited for what was ahead.

27.06–28.06 (Carla):

Our first day at Marui HQ kicked off with warm welcomes and a wave of introductions. Ms. Ibun, our project leader fluent in Japanese and English, guided us through a tour of the building. We had the honor of meeting Mr. Aoi, CEO of Marui Group, who shared his inspiring vision: a platform to connect international visitors with “Hidden Japan,” beyond the well-known paths of Tokyo, Kyoto, and Osaka.

On Day 2, we met Sybilla Patrizia, an Austrian filmmaker and the design director of the project. Her passion for local craftsmanship and storytelling brought our mission into focus. We explored how the SUKI platform could support sustainable tourism and empower regional artisans. The day concluded with a serene Zen ritual, tea ceremony, and a reflective conversation with a local priest about the tourist experience.

29.06–30.06 (Marlon):

We took the Shinkansen to Okayama and visited Kurashiki, a beautiful Edo-era town. Our goal: to interview tourists about why and how they discovered the town. Surprisingly, few foreign tourists were present, but the interviews gave us deep insights. We closed the day with dinner alongside our Marui friends.

The next day, we toured Marugo, a historic tabi shoe factory, guided by CEO Fujiki Shige-san. Watching artisans at work, and trying it ourselves, was unforgettable. We lunched with the staff and ended the day at Nishigawa Terrace, Fujiki-san’s sustainable restaurant complex. The food and heartfelt conversations reminded us how unmatched Japanese hospitality is.

01.07–02.07 (Gilles):

Day 5 was our free day. Marlon hit Nintendo World at 6 a.m., Gilles explored Kamakura, Carla wandered Kyoto, and Pierre returned to Tokyo. Day 6 was our first full-on workday: Carla and Pierre worked from HQ, Marlon and Gilles from a café. We aligned on our vision, outlined our pitches, and dove into development. The day ended with karaoke in Shinjuku that went from “just one hour” to “singing ‘til late”, the perfect team bonding moment.

 03.07–04.07 (Pierre):

Day 7 began with a creative brainstorm at Marui HQ. We shared key insights, refined our ideas, and practiced our final pitches. It was intense but energizing.

On the final day, we said goodbye to Gilles, who prerecorded his part. Presentation time came fast: the board, the SUKI team, and the CEO were in the room. No pressure! Carla and Pierre kicked it off, followed by Marlon’s pitch with virtual-Gilles via Facetime. The Q&A was rich, the feedback rewarding. We wrapped it all up with an apero and one last onsen + shabu-shabu night before heading back to Zurich.

Last fall I had the chance to do an internship in the Alpine Remote Sensing group at SLF Davos, the snow and avalanche research institute. I had just completed two years of the Computer Science Bachelor and wanted to try something new. Throughout my internship, I worked on automatically detecting and classifying avalanches in RGB webcam images. This work aims at improving avalanche monitoring by leveraging computer vision techniques, making it easier to identify hazardous conditions in real time. (RGB cameras are designed specifically to capture visible light. They create images that replicate human vision, capturing light in red, green and blue wavelengths (RGB) for accurate color representation.)

Pia Ruttner-Jansen, who supervised me during my project at SLF, works on capturing fine-grained snow-depth distributions using automated measurement stations. This data is a valuable input for assessing avalanche risk. With higher precision, preventative measures such as road closures can be shorter, more targeted, and ultimately improve safety while reducing downtime. Each station is installed high in the mountains, directly facing a slope and equipped with LiDAR sensors. Although this type of sensor produces noisier data than commercial laser sensors, it is far more affordable, making it possible to deploy multiple stations at strategic locations.

Apart from a LiDAR sensor each measurement station also has an RGB camera that is set up to take a photo every hour. While not directly used to compute snow-depth distributions these images provide an additional, underutilised stream of data. The goal of my project was to use this data to automatically detect new avalanches and reduce the time spent manually clicking through images. In addition to learning about different types of avalanches and labeling images my work mainly involved experimenting with different computer vision approaches. Two major challenges were using a noisy dataset with only a small amount of unique avalanche events and choosing a suitable task that is useful for solving the problem while allowing for the use of already labeled data.

SLF has a truly unique working culture: when it first started snowing, the head of the institute sent out an email to celebrate this with free chocolate for everyone. Many PhD students have “Jochdienst” instead of teaching duty. In a weekly rotation, they take snow measurements up at Weissfluhjoch at 7:30 a.m. whatever the weather. Fascinatingly, it is the only place at this height on earth where there have been continuous daily measurements of fresh snow and snow depth for more than 80 years!

I found it very refreshing to experience a new environment. At ETH, I would usually mostly interact with other Computer Science students. Instead, the people I met at SLF had a background in Geomatics, Geology, Electrical or Mechanical Engineering, and worked on various problems such as mapping avalanches, studying avalanche dynamics or detecting cracks in borehole images. Everyone was super nice and helpful. The amazing cafeteria constituted a great way to chat with others and find out what they are working on.

ETH Studios

ETH Studios are global innovation outposts where ETH students tackle real-world challenges alongside companies, researchers, and startups. Whether in New York, Heilbronn, Davos, or at the experimental StudioX, students gain entrepreneurial and interdisciplinary experience while contributing to sustainable and tech-driven solutions.

Contact Francesca Caggiula at eth-studios@ethz.ch if you are interested in more information on and about the ETH Studios.