
Explore exponential changes, nonlinear dynamics, and interconnected systems in ecology and economics. Gain insights on aligning individual and public good in a complex world.

Explore environment-actor interactions across various fields, from evolution to epidemics, using mathematical frameworks and simulations to understand complex systems and their impacts.

Explore the mathematical consequences of choice systems where option rankings influence selection probabilities, and popularity determines rankings, leading to potential convergence and unpredictability.

Explore the emerging science of networks, their structure, and function across diverse systems. Learn about phase transitions, interdependence, and mathematical models for predicting network behavior and consequences.

Explore global pandemics, influenza threats, and the role of mathematical modeling in disease surveillance and control through advanced computing techniques.

Explore the historical role of intelligence in physics and biology, from Laplace's demon to modern information theory, and its implications for understanding natural phenomena.

Explore a framework for machine learning to model error in dynamical systems, focusing on linear oscillators, partial information, and hybrid modeling techniques.

Explore transient dynamics in ecology, challenging classical theory focused on long-term behavior. Examine implications for modeling, management, and understanding complex ecological systems.

Explore how time-varying networks offer advantages in controllability, cooperation, and synchronization, challenging traditional views on network analysis and dynamics.

Explore curvature's role in understanding attractor dynamics and its application in time-series data reconstruction, focusing on optimal time-delay parameter selection for delay-coordinate embeddings.

Explore the H1N1 pandemic: its impact, control strategies, and mathematical modeling for prediction and prevention. Learn about public health responses and the science behind epidemic management.

Explore the theoretical foundations of urban scaling, examining how cities grow and evolve over time through complex systems analysis and mathematical modeling.

Exploring Mandelbrot's contributions to 1/f noise, long-range dependence, and fractional models. Discusses the impact of cognitive diversity on scientific progress and the importance of visual thinking in mathematics.

Explores mathematical model challenging assumptions about male mate choice and female ornamentation in polygynous species, revealing weak sexual selection on female traits despite common inferences.

Explore the power of uncertainty and contradiction in mathematics, and how these concepts can be applied to real-world situations, from disease modeling to political predictions.

Explore dimensionless similarity parameters in macroecology using Buckingham's Π theorem, presented by Sandra Chapman from the University of Warwick.

Exploring ecological theory to analyze human societies' energy use and density compared to other mammals, and modeling sustainable conditions for hyper-dense populations through green technologies.

Explores gene-culture co-inheritance of behavioral traits using a Price equation model, examining how cultural selection can overcome genetic selection and modify genetic selection pressures for complex phenotypes like altruism.

Explores how complex systems adapt to environmental patterns, favoring stable configurations that match external forces. Illustrates with toy models and swarm-robotics experiment.

Explore the patterns and dynamics of epidemic spread, examining factors that influence their shape and progression through populations.

Explore mathematical models of identity signaling, examining their impact on cooperation, conflict, and social learning in complex human behavior and communication strategies.