Filippo Radicchi

Professor
Center for Complex Networks and Systems Research
Luddy School of Informatics, Computing, and Engineering
Indiana University Bloomington

Luddy Center for Artificial Intelligence, Room 3030
1015 East 11th St., Bloomington, IN 47408

Phone: (812) 855-9322
Email: f.radicchi@gmail.com
Twitter: @filrad
Curriculum Vitae: cv.pdf

Updates

Our paper Crowding controls the scaling of bus frequency with demand has been published in PNAS

I was inducted as a Fellow of the Network Science Society

Our paper Detectability threshold in weighted modular networks has been published in Physical Review E

Our paper Shortest-path percolation on scale-free networks has been published in Physical Review E

Short bio

I am a Professor in the Luddy School of Informatics, Computing, and Engineering at Indiana University, member of the Center for Complex Networks and Systems Research, a Fellow of the Network Science Society. I am a recipient of an NSF CAREER Award and the Junior Award from the Complex Systems Society. Also, I am an Associate Editor for Physical Review E. I was a "Ramón y Cajal" senior researcher at university Rovira i Virgili, a postdoctoral researcher in the Amaral Lab at Northwestern University, and a research specialist at ISI Foundation. I have a PhD in Physics from Jacobs University Bremen, and a MS in Physics from University of Rome Tor Vergata.

Research

My research focuses on complex systems and network science. I study how network structure shapes collective behavior, how network properties can be inferred from data, and how complex networks can be optimized and controlled. More recently, I have been developing machine-learning approaches to solve optimization problems in networks, as well as studying how AI is changing social, scientific, and technological networks. See my publications or my Google Scholar profile for more info.

Selected publications

Selected recent publications

• Crowding controls the scaling of bus frequency with demand, Proc. Natl. Acad. Sci. USA 123, e2535998123 (2026)
• Task complexity shapes internal representations and robustness in neural networks, Mach. Learn. Sci. Technol. 7 025045 (2026)
• Deep-learning-aided dismantling of interdependent networks Nat. Mach. Intell. 7, 1266–1277 (2025)
• Topology shapes dynamics of higher-order networks, Nat. Phys. 21, 353-361 (2025)
• Modeling resource consumption in the US air transportation system via minimum-cost percolation, Nat. Commun. 16, 8105 (2025)
• Network community detection via neural embeddings, Nat. Commun. 15, 9446 (2024)
• Robustness and resilience of complex networks, Nat. Rev. Phys. 6, 114 (2024)
• Shortest-path percolation on random networks, Phys. Rev. Lett. 133, 047402 (2024)

Selected earlier publications

• Changing demographics of scientific careers: The rise of the temporary workforce Proc. Natl. Acad. Sci. USA 115, 12616-12623 (2018)
• Optimal percolation on multiplex networks, S. Osat, A. Faqeeh and F. Radicchi, Nat. Commun. 8, 1540 (2017)
• Percolation in real interdependent networks, Nat. Phys. 11, 597-602 (2015)
• Defining and identifying Sleeping Beauties in science, Proc. Natl. Acad. Sci. USA 112, 7426-7431 (2015)
• Abrupt transition in the structural formation of interconnected networks, Nat. Phys. 9, 717-720 (2013)
• Universality of citation distributions: towards an objective measure of scientific impact, Proc. Natl. Acad. Sci. USA 105, 17268-17272 (2008)
• Benchmark graphs for testing community detection algorithms, Phys. Rev. E 78, 046110 (2008)
• Defining and identifying communities in networks, Proc. Natl. Acad. Sci. USA 101, 2658-2663 (2004)