Dr. Hernan Makse’s APS citation reads:

“For his contributions to a broad range of topics in non-equilibrium systems ranging from urban dynamics and complex networks to statistical mechanics of jammed matter, in particular, the elucidation of the random close packing state of granular matter.”

The overarching theme of Dr. Makse’s research is the theoretical understanding of complexity. Dr. Makse’s original area of interest is the study of jammed matter, spanning from granular materials, colloidal suspensions, dense emulsions to glasses, in search of unifying theoretical frameworks. Under his 2003 NSF CAREER award, he studied statistical mechanics of particulate systems far from equilibrium. He is, however, continually coming up with new applications for the laws of physical systems, and by 2005, he was studying the dynamics of social networks under NSF auspices. Dr. Makse continues his ground-breaking work on granular matter, and, increasingly, he is applying the principles of statistical mechanics to the organization of complex networks from biological systems, to urban economics and social networks. This interdisciplinary work is at the interface of physics and disciplines such as neuroscience, biology and sociology. In recent papers he has addressed the function and evolution of protein networks, the environmental factors which may affect the spread of obesity, what makes the best spreaders of information in a social network, and a new way to define cities based on clustering algorithms from percolation theory. Dr. Makse travels the world in search of collaborators willing to take the same intellectual risks he does, and his lab at CCNY’s Benjamin Levich Institute is home to graduate students from China, Brazil, Argentina, Chile, France, Italy and the like.


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October 21st, 2020

Our quest to break down complex systems is the catalyst behind recent advances at Complex Networks and Data Science Lab, including a COVID-19 digital contact tracing app in Latin America that uses network theory

See press release at: quest to break down complex systems is the catalyst behind recent advances at Complex Networks and Data […]

August 29th, 2019

Tequila celebration of Qiongge Li PhD defense. August 2019.

April 12th, 2018

CCNY physicist tracks influence of fake news on Presidential election

    Current events have brought the spread of false information via social media to the forefront of national consciousness. […]

February 5th, 2017

Science: Predictions: The Pulse of the People

Volume 355 of Science (February 03, 2017) focuses on the use of scientific methods to predict population-level trends. The work […]

November 27th, 2016

Predicting election trends with Twitter: Hillary Clinton versus Donald Trump.

The recently-concluded United States Presidential election was the end to one of the most divisive and vitriolic campaign seasons in […]

August 6th, 2015

Nature: Optimal Percolation: Destruction perfected

NATURE | NEWS & VIEWS Nature 524, 38–39 (06 August 2015) In complex networks, some nodes are more important than others. […]

October 6th, 2014

Nature Physics: Brain Network of Networks: Why natural networks are more stable than man-made networks

Connecting complex networks is known to exacerbate perturbations and lead to cascading failures, but natural networks of networks like the […]

May 6th, 2014

MIT Tech Review: The Emerging Science of Superspreaders (And How to Tell If You’re One Of Them)

From MIT Technology Review. Nobody has figured out how to spot the most influential spreaders of information in a real-world […]

February 6th, 2014

Scientific Reports: Large cities are less green but help to reduce suicidal rates

Work done in collaboration with Jose S. Andrade from Universidade Federal de Ceara, Brazil. Large cities are more productive than […]

February 6th, 2014

Soft Matter: Fundamental challenges in packing problems: from spherical to non-spherical particles

by Adrian Baule and Hernan Makse. Random packings of objects of a particular shape are ubiquitous in science and engineering. […]