- PhD student
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).
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.
To learn more, head over to my personal website.