معرفی
Stefano Martiniani is an Assistant Professor of Physics, Chemistry, Mathematics, and Neuroscience at New York University, affiliated with the Center for Soft Matter Research and the Simons Center for Computational Physical Chemistry. His interdisciplinary research explores computational physics of complex systems, including neural circuit theories, non-equilibrium statistical mechanics, and AI-driven materials discovery. He has pioneered methods for analyzing high-dimensional energy landscapes and received prestigious awards like the NSF CAREER Award (2024) and IUPAP Early Career Prize (2023).
Education:
- PhD in Physics (2017), University of Cambridge
- MPhil in Physics (2013), University of Cambridge
- BSc in Physics (2012), Imperial College London
Research Interests: His work bridges statistical physics and artificial intelligence, focusing on:
- Engineering disordered materials with tailored spectral properties
- Quantifying entropy production in active matter
- Developing open science frameworks like ColabFit for machine learning interatomic potentials
- Neural circuit models for cortical communication
Grants & Collaborations: Funded by NSF, NIH, Chan Zuckerberg Initiative, and Simons Foundation. Leads interdisciplinary teams in computational physics, AI, and materials science.
Labs/Initiatives: Core member of NYU's Center for Soft Matter Research; develops software tools like FReSCo and KLIFF-Torch for computational materials science.
