Daniele De Martino

Daniele De Martino is a physicist specializing in statistical mechanics and its applications to biological systems. With a background in the theory of disordered systems and phase transitions, his research uses tools from statistical mechanics to analyze and model emergent phenomena in biology.

His early work addressed collective behavior in complex networks, while his recent focus has been mainly on cell metabolism, where he develops theoretical and computational methods—such  as maximum entropy inference—to study metabolic fluxes at single cell resolution. He also investigates nonequilibrium dynamics, including homeostatic feedback and oscillatory behavior in neural networks.

Daniele holds a Ph.D. in Statistical Physics from SISSA (Trieste) and obtained Postdoctoral training at the Chimera group in “La Sapienza” (Rome), at the Institute of Science and Technology (IST, Austria), and the Joszef Stefan Institute (Slovenia).
He is currently an Ikerbasque Research Associate Professor at Instituto Biofisika (UPV/EHU, CSIC) in Bilbao, where he leads interdisciplinary projects on the statistical physics of living systems