Welcome!
Hi! I’m Simon, a PhD student in artificial intelligence with Prof. Pietro Lió and the the centre for doctoral training for artificial intelligence for environmental risk (AI4ER) at the Uni of Cambridge. I know, it’s a mouthful!
I work at the intersection of artificial intelligence, biology and climate change. In particular, I reserach on using artificial intelligence to tap into biology’s potential to mitigate environmental problems (via protein design, enzyme optimisation) and on developing artificial intelligence to understand the impacts of changing environmental conditions on biological systems (protein stability, metabolic modelling).
This is my personal website and blog. I plan to use it throughout my PhD studies, mainly to practice writing about the things I learn. The blog is still under construction, so please come back for more later.
Interests
Academic Interests
I am interested in mitigating climate change and its effects, as well as biodiversity loss with the help of data science. Among my current research interests are:
- Geometric deep learning (in particular for de-novo protein design and protein engineering and understanding protein stability)
- Higher-order networks (such as hypergraphs or simplical complexes, which can be used to model important issues in systems biology)
- Bayesian Optimisation (in particular for protein design and engineering)
- Protein language models
- Carbon sequestration and photosynthesis (particularly engineering a better variant of Rubisco and the Calvin cycle)
- Energy efficient biotechnology (particularly through engineering low-temperature effective enzymes and proteins. Some enzymes extracted from bacteria are for example already used in low-temperature laundry detergents)
- Bioremediation (e.g. engineering enzymes to digest microplastics)
- Biodiversity protection (e.g. understanding the thermal limits of cold-adapted animals)
Other research that interests me, but that I am not currently persuing is related to quantum computing, quantum foundations the mathematical formalisation of causality and satellite remote sensing.
Leisure
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 improve my somewhat rusty Japanse.
Background
My original background is in theoretical and computational quantum physics, which I studied at ETH Zurich. In my physics years, I researched on various quantum technologies, such as NV-diamond quantum sensors, super-conducting qubits and on simulating U(1) quantum field theories on quantum computers at IBM Research Zurich. Studying physics made me fall in love with describing the world around us through the lense of mathematics and computing.
Physics was also how I came into contact with the artificial intelligence community. During my exchange in Japan, I pursued a pet project of classifying particle trajectories in a particle detector with deep learning. The fascination with data science stuck with me and I co-founded the Analytics Club at ETH as well as ETH’s Hack4Good programme1.
The more I leanred about artificial intelligence, the more I became intrigued by its potential in sciene and in tackling some of humanities most pressing challenges. While mathematical models may be the language of physics, artificial intelligence and learning-based systems might be the language that allows us to better understand complex emerging phenomena, such as biological and environmental systems.
After a year in industry2, I decided to follow my curiosity and return to academia to pursue postgraduate studies at the centre for doctoral training for artificial intelligence for environmental risk (AI4ER) research at the University of Cambridge.
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 fascination for artificial intelligence to help understand biology, its potential uses to tackle environmental problems and the climate change risks to biological systems.
Reach out
Feel free to reach out at simon.mathis [a] cl.cam.ac.uk if you are interested in learning more or in collaborating. I am particularly excited to help students get started in artificial intelligence for biology and environmental research. If you are a Master or Cambridge Part III student please do get in touch for potential projects. If you are doing a Master’s at a different university, feel free to get in touch nontheless as we might be able to organise a research visit at Cambridge for you via collaborators.
License
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.
If you’re curious, you can learn more about the first two editions of Hack4Good in this blog post or in this press release by the ETH industry relations. ↩
To see how working in industry compared to academia, I worked in consulting at the Boston Consulting group and as machine learning engineer at Visium, a machine learning start-up in Switzerland. ↩