About me

Hi, I’m Arthur Montanari, a postdoctoral scholar at the Center for Network Dynamics and the Department of Physics and Astronomy at Northwestern University, USA. I received the M.Sc. and Ph.D. degrees in Electrical Engineering, with a focus on control theory and nonlinear dynamics, from the Federal University of Minas Gerais, Brazil, in 2018 and 2021, respectively. From 2021 to 2022, I was a postdoctoral fellow at the Luxembourg Centre for Systems Biomedicine, University of Luxembourg, where I specialized in the development of machine learning models for biomedical data.

My current research lies at the intersection of control theory, complex systems, and machine learning, with a focus on the scalable control and design of collective behavior in large-scale networks. Recent directions include the design of large-scale neurocomputing systems (from oscillator Ising machines to coupled laser arrays and Josephson junctions), the optimal control of multi-agent systems for spatial navigation, the development of biomedical AI for heart disease prediction and drug discovery, and the vulnerability analysis of power grids.

I seek to bridge theory with applications in physical, biological, and technological systems, and I’m always looking for new theory-experiment-data collaborations! I’m now working on unconventional computing approaches for model learning & training, with the goal of advancing both attention mechanisms and energy efficiency in neural dynamical systems.

Selected publications

AN Montanari, AED Barioni, C Duan, AE Motter. Optimal flock formation induced by agent heterogeneity. Nature Communications, in press (2025).

AN Montanari, C Duan, LA Aguirre, AE Motter. Functional observability and target state estimation in large-scale networks. Proceedings of the National Academy of Sciences of the U.S.A, 119: e2113750119 (2022).

ME Gavidia, H Zhu, AN Montanari, J Fuentes, …, X He, X Yang, J Gonçalves. Early warning of atrial fibrillation using deep learning. Patterns, 5:100970 (2024).

MM Garcia, A Aalto,  AN Montanari, A Skupin, J Gonçalves. Multi-omic network inference from time-series data. npj Systems Biology and Applications, 11:114 (2025).

AN Montanari, C Duan, AE Motter. Duality between controllability and observability for target control and estimation in networks. IEEE Transactions on Automatic Control 70:5584-5591 (2025).