Research Team

PhD Students

Alvaro Lanza-Serrano

Alvaro Lanza

I studied physics at Durham University, graduating with an MPhys, and completing computational research on magnetic skyrmions and confined active matter.
My fascination with the latter drove me to an M2 Masters degree on Physics of Complex Systems, at Sorbonne Université. My experience here learning about the origins of various emergent phenomena, and the powerful tools stochastic thermodynamics provides for analysing the non-equilibrium dynamics of processes that are fundamental to life itself, fully cemented my desire to embark on a PhD in the field. Thus, after an internship at the Gulliver Lab (ESPCI) on simulated active solids, in Oct 2023 I began a PhD on "nonequilibrium thermodynamics of fluctuating living systems". I am especially interested in developing analytical descriptions of these systems and their experimental testability.

Xiang Qu

Xiang Qu

I completed my undergraduate studies at Hunan University, where I conducted research on 'Segmentation and Pointwise Inference of Anomalous Diffusion Trajectories Using Deep Learning.' The application of machine learning significantly improved the ability to infer key parameters of anomalous diffusion, which sparked my curiosity about why machine learning is so effective in this context. As a result, in October 2024, I began my PhD studies, driven by a desire to explore explainable machine learning and its potential applications in active matter systems. My goal is to bridge the gap between machine learning models and their interpretability, while contributing to the growing understanding of active matter dynamics.

Alumni