Personnel

Talk by Prof. Makse at the Pujiang Forum on Innovation organized by Nature Physics in Shanghai, October 30-31, 2018. Talk of Prof Makse starts at 6:00 minutes.

Our research is related to “emergent properties”, i.e., “properties not contained in the simple laws of physics, although they are a consequence of them” (Phil Anderson, 1971, “More is different“).

As Schopenhauer¹, we  conclude that “it is as though our lives were the features of the one great dream of a single dreamer in which all the dream characters dream, too; so that everything links to everything else, moved by the one will to life which is the universal will in nature.”

By Joseph Campbell on Schopenhauer:

¹Schopenhauer, A. Transcendent Speculation on the Apparent Deliberateness in the Fate of the Individual, in Parerga and Paralipomena:  Short Philosophical Essays, Vol. I, pp. 199-225 (Oxford University Press, Oxford, 1974).

“It’s the research we do that counts, not the journal”:

Openings


Our group has openings for graduate students to work on granular matter and complex networks, broadly considered. For an account of the daily routine for students in our lab, see the report of Louis Portal, research intern from France.

Graduate students and postdocs working in our group are expected to be (or become) familiar with the following computing systems. There are also a number of pertinent videos here, by presenters at the NIPS conference.

For background on the research areas of the various group members, please click here.

Director

Hernán Makse currently serves as Professor of Physics at City College of New York, wherein he is responsible for the Complex Networks and Soft Matter lab at the Levich Institute. He is also a Member Affiliate, Attending Imaging Scientist, MSKCC Rank at Memorial Sloan Kettering Cancer Center. He holds a PhD degree in Physics from Boston University. He has been author of numerous publications on the theory of complex systems and the physics of soft materials and he is an APS Fellow. His research focuses on the theoretical understanding of Complex Systems from a Statistical Physics viewpoint. He is working towards the development of new emergent laws for complex systems, ranging from brain networks to biological networks and social systems.  Treating these complex systems from a unified theoretical approach, he uses concepts from statistical mechanics, network and optimization theory, artificial intelligence, and big-data science to advance new views on complex systems and networks.

Ph.D. Students

IMG_8674

Ian Leifer

Symmetries and machine learning in biological networks

<ianleifer93@gmail.com>

Luis Alvarez

Symmetries and computation in biological networks.

<luisalvarez.10.96@gmail.com>

Bryant Avila

Complex networks

<kryogenica@gmail.com>

Visiting Students

微笑时刻证件照

Jiannan Wang, Beihang University

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Zhenhua Wang, East China Normal University

Undergraduate Students

Louis Portal, ’13

Louis Portal <marshallportal@yahoo.fr>

Alumni

IMG_2248

Kate Burleson-Lesser, 2018

Eye-tracking, critical phenomena, stock market inference

<skippyandjif@gmail.com>

Shaojun Luo, 2018

Social networks, Big Data analytics

<sjlocke.1989@gmail.com>

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Qiongge Li, ’19

Cancer-affected brain networks

<lqiongge@gmail.com>

Projects of Current Students and Postdocs:

 

Flaviano Morone flaviomorone@gmail.com Complex network theory. Spin glasses. Collective Influence. A model of brain activation predicts the collective influence map of the human brain
Alexandre Bovet alexandre.bovet@gmail.com Complex network theory. Social networks. Predicting election trends with Twitter: Hillary Clinton versus Donald Trump
Byungjoon Min min.byungjoon@gmail.com Complex network theory. Brain analysis. Searching for influencers in big-data complex networks
George Furbish geofurb@scarletmail.rutgers.edu Social media. Influencers. Big data analytics.
Qiongge Li  lqiongge@gmail.com Cancer-affected brain networks.
Kevin Roth rothk@student.ethz.ch Network of networks. Brain network theory. Emergence of Robustness in Network of Networks
Shaojun Luo sjlocke.1989@gmail.com Big data analytics in social networks. Inferring Personal Finanacial Status from Social Network Location
Lingchen Bu lingchen.l.bu@gmail.com Brain network inference.
Muhua Zheng zhengmuhua163@gmail.com Percolation in the brain.
Teng Xian xianteng.buaa@gmail.com Superspreaders. Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks
Kate Burleson-Lesser skippyandjif@gmail.com Eye-tracking. Critical phenomena and inference. Stock market inference. Collective Behaviour in Video Viewing: A Thermodynamic Analysis of Gaze Position
Zhuo Yin zhuoyin.enjoy@gmail.com Econophysics. Stock market inference.
Eru Kyeyune-Nyombi eru.nyombi@gmail.com Colloidal jamming systems. Experiments. High-resolution of particle contacts via fluorophore exclusion in deep-imaging of jammed collodial packings
Francesca Arese Lucini francesca.areselucini@gmail.com Brain networks.
Ian Leifer ianleifer93@gmail.com Complex networks.