I am fascinated by randomness, how it impacts living systems, and the strategies to cope with it and exploit it. How do living systems deal with fluctuations without being overwhelmed by them? How do cells manage to employ their stochastic machinery to process noisy signals and nonetheless perform tasks reliably? How much does this cost them? How can we exploit fluctuations to design efficient microscopic engines?
These are a few of my favourite questions that drive my research at the interface between statistical physics and biology. In investigating them, I make use of tools from stochastic processes, non-equilibrium thermodynamics, stochastic optimal control, information theory, and machine learning. These tools often steal the stage and developing them becomes the focus itself.

Here you can find a video summarising our recent results on the stochastic motion of single molecules in biomolecular condensates.

Open Positions

• PhD position on an exciting project to use statistical physics and machine learning to study force-sensing proteins. The project is interdisciplinary and involves the possibility of doing experiments in the lab of Rafel Tapia-Rojo and developing molecular dynamics simulations under the supervision of Chris Lorenz. The position's start date is June 1st 2025. The deadline for applying is on January 31st.
  Apply here!
  Informal enquiries are welcome, just email me.