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About me

Hi, I’m Simon Mathis, a postgraduate student in environmental data science at the University of Cambridge. This is my personal website and blog. I plan to use it throughout my PhD studies, mainly as a way of forcing myself to practice writing about the things I learn.

At the moment the site is still under construction, so please come back for more later.

My background

My original background is in theoretical and computational physics at ETH Zurich. Now, I pursue my postgraduate studies in environmental data science at the centre for doctoral training for artificial intelligence for environmental risk (AI4ER) research at the University of Cambridge. Next to my research, I engage in the Swiss tech startup Visium, where I head the non-profit projects and develop the sustainabilty strategy.

For my master’s thesis in physics I worked on simulating U(1) quantum field theories on quantum computers at IBM Research Zurich. While I love theoretical quantum physics, I realised that working in an interdisciplinary environment on topics of immediate relevance to humanity’s challenges motivates me even more. A topic I care particularly about is climate change. My PhD at the AI4ER CDT at Cambridge allows me to sit in the sweet spot of my interests: It allows me to use my passion for mathematics by developing data-science tools for envrionmental research in an interdisciplinary context.

I came in contact with data science comparatively late, i.e. when the deep learning revolution was already in full swing. At the time I pursued a pet project of classifying particle trajectories in a particle detector with deep learning as a small research project on the side during my exchange in Japan. The fascination with data science stuck with me and I co-founded the Analytics Club at ETH as well as ETH’s Hack4Good programme. If you’re curious, you can learn more about the first two editions of Hack4Good in this blog post I wrote back in 2019 or in this press release by the ETH industry relations.



I am interested in mitigating climate change and its effects, as well as biodiversity loss with the help of data science. As I am still fairly new to the environmental sciences side of things, I am currently exploring different opportunities.

Among my research interests so far are:

  • Deep Learning (in particular for the emulation of physical systems and in vision for remote sensing)
  • remote-sensing (particularly from space)
  • carbon sequestration
  • biodiversity protection

An interesting fact that I recently learned is that while forests sequester a massive amout of carbon, forest fires anually emit around 8 billion tons of CO2 per year. This compares to about 36 billion tons of CO2 emitted annually from fossil fuels by humans. In other words, if forest fires were a country, they’d be the second largest emitter (after China). This made me wonder about the potential to save gigatonnes of carbon emissions per year by improving forest fire mitigation.

Other research that interests me, but that I am not currently persuing is related to quantum computing, quantum foundations and the mathematical formalisation of causality.


In my leisure time I like to practice Aikido or do outdoor sports such as climbing or skiing. Indoors, I enjoy reading and learning languages. After having spent an amazing exchange semester in Tokyo, my latest language project is to learn Japanse.


I’m using Jekyll to serve my blog via Github Pages. The theme is from Chirpy. The favicon is calligraphy by suib icon from the Noun Project.


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