Welcome to the Out of Equilibrium Group
The Out of Equilibrium Group @ UML explores the physics of systems driven far from equilibrium, from quantum computation to active matter. Our research connects statistical mechanics, topology, and machine learning to understand how complexity, information, and order emerge in dynamic environments.
Current themes include superstatistics, quantum and classical machine learning (including quantum-enhanced Boltzmann machines and quantum control), anyons and time crystals, out-of-equilibrium thermodynamics, entropy production, dissipation, and active matter self-organization.
We apply these ideas to both fundamental physics and real-world problems, from quantum sensing to biomedical imaging.
We are looking for passionate new PhD students, Postdocs, and Master students to join the team !
News
Fall 2026
Congratulations to Arthea on being accepted into the MMSc in Biomedical Informatics program at Harvard Medical School 
July 2026
Congratulations to Michael on the publication of his paper, Focal Plane Wavefront Correction for Dark Hole Creation with a Neural Network on PICTURE-D in the SPIE Proceedings! Michael traveled to Copenhagen, Denmark, to present this cutting-edge machine learning research at the SPIE Astronomical Telescopes + Instrumentation 2026 conference.
December 10 2025
Congratulations to Opeyemi and Jack! Their Mini-Review, Synergizing Driven Quantum Dynamics, AI, and Quantum Computing for Next-Gen Materials Science has been named one of the most popular articles in The Journal of Physical Chemistry Letters!