The series' main focus is the study of complex systems ranging from collective cellular behavior to dense crowds. It will cover both a networked approach to the modeling and analysis of these complex systems as well as a continuum one.
The activities will start with a course offered by Prof. Sidney Redner of Santa Fe Institute on out-of-equilibrium processes introducing random walks, birth and death processes, aggregation, and complex networks' models. [Jan. 23, 25, 26, 30, Feb. 1 and 3, 2023]
The week of February 13th will cover the continuum limit and the theoretical toolbox to studying multiscale collective behavior in which Prof. Sriram Ramaswamy of the Indian Institue of Science (IISC) will be giving a short course on the Hydrodynamics of Active Matter. [Feb. 13, 15 and 17, 2023]
The mini-course will be followed by lectures and hands-on on Data-Driven Modal Decompositions by Prof. Miguel Alfonso Mendez of the von Karman Institute. [Feb. 23 and 24, 2023]
Prof. Marcello del Castillo Mussot (UNAM, Mexico) will be visiting CAMS and will hold a workshop on the study of Networks and Conflict and will take in students to embark on a data-driven approach to temporal and spatial statistical analysis of the Network of the Drug Cartels in Mexico.
Organized by Dr. Sara Najem (Department of Physics) under her CAMS Fellowship.
Upcoming Courses
- Comunity Aware Centrality in Complex Networks by Prof. Stephany Rajeh (Laboratoire d'Informatique de Bourgogne, France)
- Date and Time: TBA
- Venue: Department of Physics, room 219 and Zoom.
Previous Events
Courses and Workshops
- Nonlinear Dynamics of Complex Systems - Multi-Dimensional Time Series, Network Inference and Nonequilibrium Tipping by Prof. Marc Timme (Institute for Theoretical Physics & Center for Advancing Electronics Dresden (cfaed), TU Dresden) - [Poster]
- Date and Time: March 9 at 3:00pm , March 10 &14 at 4:00pm and March 23 at 3:00pm
- Venue: College Hall, Auditorium B1 and Zoom.
- Recorded lectures:
- Abstract:
The dynamics of natural and engineered networks enables the function of a variety of systems we rely on every day, from metabolic circuits in the cell and neural networks in the brain to electric power grids and water supply networks. To date, it remains unclear how to extract key features of networks if only time series data from (some) units are available. Often it is even hard to predict qualitative changes in the system dynamics, such as the crossing of a tipping point, if a complete model of the system is given. Here we report on recent progress on making such predictions. We start with the problem of detecting structural features from observed dynamics [1-5] and end at the frontier of research on predicting tipping points [6]. First, we demonstrate how to identify the number N of dynamical variables making up a network -- arguably its most fundamental property -- from recorded time series of only a small subset of n<N variables. Second, we introduce several approaches of uncovering network topological features from observed nodal time series data. Third, we demonstrate that and why standard perturbation theories (at any order) are intrinsically incapable of predicting tipping points from the time evolution rules of nonequilibrium externally driven systems and propose a novel perspective to quantitatively characterize their genuinely nonlinear response properties.
- Footnote:
The work underlying these lectures have been jointly undertaken with Jose Casadiego, Mor Nitzan, Hauke Haehne, Georg Boerner, Benjamin Sauer, Moritz Thuemler and others.
[1] Topical Review: Marc Timme & Jose Casadiego, J. Phys. A 47:343001 (2014).
[2] Casadiego et al., Nature Comm. 8:2192 (2017).
[3] Nitzan et al., Science Adv. 3:e1600396 (2017).
[4] Haehne et al., Phys. Rev. Lett. 122:158301 (2019).
[5] Boerner et al., in prep. (2023).
[6] Thuemler et al., IFAC 55:254 (2022), special issue of the 25th Intl. Symp. Math. Theory Netw. Syst.
- Networks and Conflict by Prof. Marcelo del Castillo-Mussot (Physics Institute, UNAM, Mexico) - [Poster]
- Date: February 21, 28 and March 2, 2023 ***Lecture on February 21 is resceduled to Saturday, February 25 at 10:00am at Nicely 211***
- Time: 2:00pm Beirut Time
- Venue: College Hall, Auditorium B1 and Zoom.
- Recordings:
- Data Driven Modal Decompositions in Fluid Dynamics by Prof. Miguel Alfonso Mendez (Von Karman Institute for Fluid Dynamics, Belgium) - [Poster]
- Dates: February 23 and 24, 2023
- Time: 3:00pm Beirut Time.
- Venue: Department of Physics, room 219 and Zoom.
- Recording:
- Active Hydrodynamics in Complex Systems by Prof. Sriram Rajacopal Ramaswamy (Indian Institute of Science, India) - [Poster]
- Dates: February 14, 16 and 17, 2023.
- Time: 2:30pm Beirut Time.
- Venue: College Hall, Auditorium B1 and Zoom.
- Recordings:
- Networked Complexity by Prof. Sidney Redner (Santa Fe Institute, USA) - [Poster]
- Course Outline:
- Introduction to Random Walks
- Kinetics of the Birth/Death Process
- Kinetics of Aggregation
- Complex Networks
- Dates: January 23, 25, 26, 30, February 1 and 3, 2023.
- Time: 5:15pm Beirut Time.
- Venue: College Hall, Auditorium B1 and Zoom.
- Recordings:
Lecture Series on Networked Complexity:
- Peter Klimek (Medical University of Vienna) - [Poster]
- Title: Network Medicine: The Healthcare System as a Complex System
- Date and Time: July 18 at 3:00pm
- Venue: COllege Hall, Auditorium B1 & Zoom
- Samir Suweis (University of Padova) - [Poster]
- Title: Resilience of the Global Food System: a Complex Network Approach
- Date and Time: July 25 at 4:00pm
- Venue: College Hall, Auditorium B1 & Zoom
- Recorded Lecture: https://youtu.be/eC1G_6wLvWY
- Sara Najem (Department of Physics, American University of Beirut) - [Poster]
- Title: Networked Complexity from Living Cells to Urban Systems
- Date and Time: June 6 at 3:00pm (Beirut time)
- Venue: College Hall, Auditorium B1
- Recorded Lecture: https://youtu.be/5y6noQUesaQ