we are in the midst of a rapid emergence in the use and dependence on cyber physical systems (cps). these systems are becoming increasingly integrated into critical infrastructure, health systems, defense capabilities, manufacturing processes, and personal property. this book explores how the thoughtful and creative application of modeling and simulation can exploit the potential of cps while guarding against risks. the author touches upon three topics: timescale challenges, conceptual expectations, and workforce shortage. in addition to balancing the inherent complexities of embedding computing into the physical world, there is a need to address both legacy components and processes as well as new systems. the need for cps solutions to be reliable, safe, scalable, and adaptable exacerbates this challenge. the incorporation of legacy components creates a system with parts having greatly differing lifetimes. modeling and simulation approaches described in this text offer a strategy to design, predict, and analyze the effects of these multi-time-scale components. further, while the techniques described in this text allow modeling of the ecosystem as a whole and details at the component level, one may consider the expectations and limitations of automated cps. for example, there is a strong motivation in the machine learning community to incorporate assurance and explainability. when applied to autonomous vehicles, this partially translates to a desire to understand why decisions were made that resulted in an accident. when we remove the autonomous component of the system and look at human-driven accidents, we realize that humans do not excel at identifying the causes of a vehicular accident when they are the driver of the accident. similarly, it is challenging for humans to identify the intent of another system and yet we may ask our cps their intentions. echoing horowitz’s words in the foreword to this text, one of the challenges associated with this field is the recognized shortages of people that can develop and/or employ these complex analysis techniques to cps. if we broadly define the relevant technical backgrounds of scientists and engineers that will impact this field as math, computer science, physics, psychology and social sciences, and engineering, we can track the trends of graduate degrees awarded in these fields. figure e.1 displays this most recent data on phd graduations over a period of five years, by broad field of study. this plot demonstrates a modest, 7%, increase in these targeted graduations over the five year time period. thus, it is an unanswered question of whether the workforce shortage challenge will persist. this cross-disciplinary text brings together a variety of points of views from experts in the field of modeling and simulation for cps with a diverse technical background, and offers the opportunity to develop the expertise of the needed developers and researchers as well as build upon the expertise of those with related skillsets.we are in the midst of a rapid emergence in the use and dependence on cyber physical systems (cps). these systems are becoming increasingly integrated into critical infrastructure, health systems, defense capabilities, manufacturing processes, and personal property. this book explores how the thoughtful and creative application of modeling and simulation can exploit the potential of cps while guarding against risks. the author touches upon three topics: timescale challenges, conceptual expectations, and workforce shortage. in addition to balancing the inherent complexities of embedding computing into the physical world, there is a need to address both legacy components and processes as well as new systems. the need for cps solutions to be reliable, safe, scalable, and adaptable exacerbates this challenge. the incorporation of legacy components creates a system with parts having greatly differing lifetimes. modeling and simulation approaches described in this text offer a strategy to design, predict, and analyze the effects of these multi-time-scale components. further, while the techniques described in this text allow modeling of the ecosystem as a whole and details at the component level, one may consider the expectations and limitations of automated cps. for example, there is a strong motivation in the machine learning community to incorporate assurance and explainability. when applied to autonomous vehicles, this partially translates to a desire to understand why decisions were made that resulted in an accident. when we remove the autonomous component of the system and look at human-driven accidents, we realize that humans do not excel at identifying the causes of a vehicular accident when they are the driver of the accident. similarly, it is challenging for humans to identify the intent of another system and yet we may ask our cps their intentions. echoing horowitz’s words in the foreword to this text, one of the challenges associated with this field is the recognized shortages of people that can develop and/or employ these complex analysis techniques to cps. if we broadly define the relevant technical backgrounds of scientists and engineers that will impact this field as math, computer science, physics, psychology and social sciences, and engineering, we can track the trends of graduate degrees awarded in these fields. figure e.1 displays this most recent data on phd graduations over a period of five years, by broad field of study. this plot demonstrates a modest, 7%, increase in these targeted graduations over the five year time period. thus, it is an unanswered question of whether the workforce shortage challenge will persist. this cross-disciplinary text brings together a variety of points of views from experts in the field of modeling and simulation for cps with a diverse technical background, and offers the opportunity to develop the expertise of the needed developers and researchers as well as build upon the expertise of those with related skillsets.