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)
- Gauge-invariant quantum circuits for \(U(1)\) and Yang-Mills lattice gauge theories.
Mazzola, G., Mathis, S. V., Mazzola, G., & Tavernelli, I. (2021). Physical Review Research, 3(4), 043209. [arxiv]
- Toward scalable simulations of lattice gauge theories on quantum computers.
Mathis, S. V., Mazzola, G., & Tavernelli, I. (2020). . Physical Review D, 102(9), 094501. [arxiv]
Past research projects
- Master thesis: Resource estimates for simulating \(U(1)\) lattice gauge theories on quantum computers at ETH Zurich and IBM Research Zurich. Paper.
- Side project: Simulating quantum thought experiments on a computer.
The project is geared in particular towards simulating the Frauchiger-Renner paradox and formalizing interpretations of quantum mechanics in mathematical language. Unfortunately I haven’t yet found the time to fully finish this project. Project Code.
- Bachelor thesis: I created meta materials for producing slow light in the microwave domain at ETH’s qudev lab. By engineering the photonic band gap using different inductances and capacitances, we managed to delay the light by two orders of magnitude compared to a transmission line of the same length. Our technique can for instance be used to create on chip delay lines for qubit-qubit communication or to engineer a photonic bandgap. Report.
- Bachelor proseminar: An introduction to quantum dissipation. Report.