
Explore nonlinearities in black-hole ringdowns with experts Keefe Mitman and Saul Teukolsy, delving into advanced concepts in gravitational physics and astrophysics.

Explore how network architecture influences and constrains dynamics in recurrent neural networks, focusing on threshold-linear models and their implications for understanding connectomes in neural computation.

Explore physical reservoir computing for embedding bifurcation structures in autonomous dynamics of soft bodies, focusing on innovative machine learning applications in dynamical systems.

Discover innovative approaches to analyze cancer progression using machine learning and dynamical systems, bridging static imaging data with dynamic biological processes.

Explore the future of human-landscape interactions, discussing driving forces, global shaping, and sustainability challenges in the Anthropocene era.

Explore cutting-edge research on nonlinear and scaling processes in atmospheric and oceanic systems, covering climate reconstructions, sensitivity, long-range memory, megadroughts, turbulence, and micro-scale phenomena.

Explore non-power-law restoring forces in oscillating systems, extending simple harmonic motion concepts to more complex scenarios using computational tools and visual simulations.

Explore double pendulum dynamics with Poincaré maps, analyzing different length ratios and their impact on chaotic behavior using VPython simulations.

Explore biological network dynamics and design, focusing on specific case studies. Gain insights into complex systems and their applications in theoretical approaches to cancer research.

Explore systems biology approaches to unravel cell cycle dynamics, focusing on mathematical modeling and computational techniques to understand complex cellular processes.

Explore mammalian cell cycle regulation modeling techniques, focusing on theoretical approaches to understand cancer progression and treatment. Gain insights into advanced mathematical and computational methods.

Explore systems-level analysis of phenotypic switching in melanoma, focusing on design principles and their implications for understanding cancer progression and developing targeted treatments.

Explore coupled oscillators and matrix applications in physics. Gain insights into theoretical aspects through hands-on experiments and open-ended discussions. Designed for women pursuing physics careers.

Explore biological dynamics using physics tools to model predator-prey oscillations, ecosystem chaos, and microbial swimming. Learn to predict species competition, population changes, and collective behavior in fluids.

Explore biological dynamics using physics tools to model complex living systems, from predator-prey oscillations to bacterial motility, in this introductory course for undergraduates.

Explore biological dynamics using physics tools to model predator-prey oscillations, ecosystem chaos, and microbial swimming. Learn to predict species competition, population changes, and collective behavior in fluids.

Explore biological dynamics using physics tools to model predator-prey oscillations, ecosystem chaos, and microbial swimming. Learn to predict species competition, population changes, and collective behavior in fluids.

Explore data assimilation in Earth sciences, focusing on dynamical systems and their applications in weather and climate modeling. Learn theoretical foundations and practical implementations.

Explore data assimilation in Earth sciences, covering theory, methods, and applications in weather, climate, and environmental monitoring. Gain hands-on experience with various techniques and uncertainty estimation.

Explore data assimilation theory and applications in Earth sciences, focusing on dynamical systems. Gain hands-on experience with practical techniques for integrating observations and forecasts in weather and climate models.

Annual discussion meeting for Indian statistical physics community, covering diverse topics from quantum fluids to complex systems. Fosters collaboration among scientists, postdocs, and students in the field.