Prof. Baruch Barzel

Head of Research Lab

    Full CV:


    Ph.D.  Physics, Hebrew University of Jerusalem, Israel

    M.Sc.  Physics, Hebrew University of Jerusalem, Israel


    Senior Lecturer   (Assist. Prof.) Bar-Ilan University, Mathematics Department, Israel

    Core faculty member Bar-Ilan Data Science Institute


    2016 Visiting Professor | Network Science Institute, Northeastern University, Boston, MA.

    ​2015 Visiting Professor | Network Science Institute, Northeastern University, Boston, MA.

    ​2013 –2014 Postdoctoral Research Associate | Channing Division of Network Medicine, Harvard Medical School, Boston, MA.

    ​2010 –2013 Postdoctoral Research Associate | Center for Complex Network Research, Northeastern University, Boston, MA.


    2019 Krill Prize for Excellence in Scientific Research, Wolf Foundation

    2019 Rector Prize for Scientific Innovation

    2018 Outstanding lecturer award

    2017 - 2018 ERASMUS Plus grant for exchange of knowledge and travel

    2007 - 2010 The Harry and Sylvia Hoffman Leadership & Responsibility Program

    2007 Giulio Racah award for excellence in research, Israel

    2005 - 2010 Outstanding teacher award (5 consecutive years), Hebrew University of Jerusalem ​




    Dynamics of Complex Networks

    Statistical physics is the theory of interacting particles, gases and liquids. Its way of thought, however, goes beyond the domain of material science. In a broader perspective it provides us with a bridge between the microscopic description of a system and its observed macroscopic behavior. With it we can track the way in which system-level phenomena emerge from the mechanistic description of the system’s interacting components. For instance how the blind interactions between pairs of magnetic spins lead to the seemingly cooperative phenomena of magnetism.

    At CND we develop the statistical physics of complex systems: our interacting particles are not atoms or spins, but rather genes, proteins, animal species or humans. We track the way in which individual human interactions lead to the spread of ideas, perceptions and also diseases, or how biochemical reactions between proteins transfer information between cellular components. These systems defy many of the classic principles that are central to the way physics is traditionally done. The particles are self-driven and non-Newtonian, the interactions are nonlinear and the underlying geometry in random, highly irregular and non-localized. In two words – complex systems.

    With these challenges at hand, we find that the dynamic behavior of these complex systems – social, biological or technological – can be predicted, analyzed and understood using the tools and way of thought of statistical physics.

    Last Updated Date : 25/06/2022