The Science of ResilienceEdition 1

"This is a book that approaches resilience as a systems problem, examined through models, analogies and worked examples drawn from physics, ecology, engineering, finance and cyber security…  By using mathematical models and real-world examples, the book provides practical tools and strategies for designing resilient systems that can adapt and thrive in the face of uncertainty."
- "Inspiration for Resilience Professionals." CIR Magazine, Q1 2026. https://www.cirmagazine.com

Strategies for improving resilience, incorporating complexity theory, risk analysis, and systems thinking with a rigorous mathematical treatment

The Science of Resilience delves into the fascinating field of resilience science, exploring how various systems, ranging from physical infrastructure to social networks, can withstand and recover from disruptions. This interdisciplinary subject combines principles from complexity theory, risk analysis, and systems thinking to understand and mitigate the impacts of events like natural disasters, cyber-attacks, and economic crises. By using mathematical models and real-world examples, the book provides practical tools and strategies for designing resilient systems that can adapt and thrive in the face of uncertainty.

Written by a highly qualified author with significant experience in the field, this book:

• Covers synchronization, bottleneck analysis, epidemic modeling, social network disinformation and how to counter it, and restructuring a system to increase resilience
• Explains phase change and shows how to apply it to general complex systems
• Integrates rigorous mathematical models with real-world applications through mini case studies and hypothetical examples covering physical, economic, and social systems
• Provides tools and strategies to design resilient systems, analyze potential risks, and plain for resilience

Addressing an important gap in risk and resilience literature, this book offers valuable insights for engineering and systems design professionals, complexity science and risk analysis researchers, and graduate students in related fields, as well as anyone interested in the science of resilience.