About me

Research Vision

I wander between the fields of machine learning and cryospheric sciences. I am currently obtaining a formal education on ML, however, I am striving to require knowledge also outside if the classroom. When joining a project, I make sure to participate in field-work, and the hands-on work done by my collaborators. This way I can understand where our data comes from, the hardships attached to its collection, and its socio-cultural context.

My research values are centered around 1) open science, 2) interdisciplinary collaboration, and 3) real-world impact. When I am joining a project, I want to get in touch with every aspect of the project, ranging from understanding the math, the code, the hardware, the data, the people, and the places involved. In my opinion, such a holistic approach to applied ML creates better models, and larger impact.

Privileges & Discrimination

I am white woman from an academic household, born into a rich country (Germany). I am also a queer woman with a chronic blood disease. Where I can, I try to extend my privileges to others.

Please feel always free to reach out to me if you consider yourself as a member of an underrepresented or discriminated group in the ML or cryospheric community and have specific requests of how I can support you. This can range from reviewing CVs and applications, to talking through questions such as “how can I find my way into those communities?”. When you get in touch with me, there is no need to explain or justify in which way you consider yourself discriminated.

Long Bio

I was born in Europe, and spent my childhood and young adult years in Germany, Switzerland, and Italy. I studied Cognitive Science in Osnabrück, because I was curious about everything and the program exposed me to numerous disciplines, ranging from philosophy to computer science. To my own surprise, coding and solving AI puzzles became quickly my personal highlights of the program. I was thrilled when I got the chance to be a TA for two of the AI & logic programming courses. In order to figure out if I like research, I got involved in Dr. Leonid Berov’s project teaching models how to tell good stories (also, I am a big fantasy book lover). I got more research exposure at the INRS in Quebec under the supervision of Prof. Taha Ouarda. In the same year, I also went to Tokyo for an exchange semester. It gave me the possibilty to learn how education and academia looks like in a culture that was new for me and explore different ways of living. For my bachelor thesis, I followed my passion for snow and ice, and thus worked together with Dr. Amy Macfarlane, Dr. Viviane Clay, and Dr. Martin Schneebeli to segment and classify snowpack profiles with ML models. Those measurements have been collected during MOSAiC, the largest polar expedition of our history. After my BSc thesis I worked for a couple of months with Dr. Lenka Novak under the supervision of Prof. Tapio Schneider to track extra-tropical cyclones with Fourier Neural Operators. At this point, I already knew I wanted to combine my joy for coding with my desire to protect and understand our planet.

To follow that path, I joined Prof. David Rolnick’s lab (Climate Change AI founder) as a research MSc student at McGill University & Mila in 2021. During my MSc I focused on emulating climate models with machine learning, resulting in the dataset paper ClimateSet. In 2023, I fast-tracked to the PhD program. While still engaged in climate emulation with ML, I am nowadays focusing on Machine Learning for the Cryosphere. The Cryosphere is calling, and I will see within the next years if I find my tools helpful enough to understand and mourn the disappareance of its beauty.

Since January 2024, I am in Davos and involved in the model development, data campaign planning and data collection for a new measurement device engineered by Tiziano Di Pietro. Subsequently, we want to train a new ML model to predict snowpack stability in-situ. We belief that this project has the potential to become highly impactful for in-situ avalanche warning teams.

Beyond research, I identify myself strongly by being emerged, learning from and fighting for nature. I have been involved in climate activism since I am 14 years old. Recently, in summer 2023, I traversed the Juneau icefield as part of field-educational expedition program. I did that to learn from nature in nature. It gave me access to and a whole new understanding of our cryosphere and substantially changed my way of developing and applying ML models for the cryosphere.

I am encouraging everyone who has the possibility to engage in field work and science support to learn where your data comes from, why ground truth is almost never ground truth, and connect with the communities you want to serve with your science.