Regular biography
Stefano Martiniani is an Assistant Professor of Physics, Chemistry, and Mathematics at New York University, affiliated with the Department of PHY. He is a core member of NYU's Center for Soft Matter Research and the Simons Center for Computational Physical Chemistry, and an affiliate of the Center for Data Science. His research focuses on the computational and statistical physics of complex systems, including neural circuit theories of brain function, the statistical mechanics of systems far from equilibrium, high-dimensional energy landscapes, disordered metamaterials, and AI for science. He leads open science initiatives related to data standards, data repositories, and machine learning frameworks. His work includes pioneering techniques to determine the volume of high-dimensional basins of attraction and advancing the understanding of bacterial rectification. His research is supported by the NSF, NIH, Chan Zuckerberg Initiative, and the Simons Foundation.
Scholar-generated biography
Stefano Martiniani is a researcher at New York University with expertise in Statistical Physics, Computational Physics, Neural Systems, and Machine Learning. His work explores the intersection of these fields, focusing on the development and application of machine learning techniques to problems in physics and materials science. He has published extensively on topics such as energy landscapes for machine learning, interatomic potentials, and the statistical mechanics of jammed systems. His research also includes studies on active matter, entropy production, and the design of force fields for molecular simulations. Martiniani's contributions span both theoretical and computational approaches to understanding complex physical systems.