Complex Adaptive Systems Science, PhD

Program Overview

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The Complex Adaptive Systems Science PhD program at Arizona State University provides students with a unique opportunity to gain a deeper understanding of the complexities inherent in natural and human systems. This interdisciplinary program emphasizes collaboration and transdisciplinary methodologies, enabling students to transcend traditional boundaries and approach challenges with an integrated perspective. Graduates will be equipped with the knowledge, skills, and tools needed to investigate, analyze, and model complex adaptive systems across a wide range of disciplines, preparing them for diverse and impactful careers in sustainability, social sciences, life sciences, physical science and engineering, data science and technology, and academia.

Program Outline

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Degree Overview:

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Program Description:

The Complex Adaptive Systems Science (CAS) PhD program at Arizona State University provides students with a unique opportunity to gain a deeper understanding of the complexities inherent in natural and human systems, and how these systems influence and interact with one another. This program emphasizes interdisciplinary collaboration and transdisciplinary methodologies, enabling students to transcend traditional boundaries and approach challenges with an integrated perspective. By understanding complex systems through the lens of CAS principles and approaches, graduates will have the potential to affect positive changes across various domains, contributing significantly to society's overall progress.

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Objectives:

The PhD in CAS aims to:

• Equip graduates with the knowledge, skills, and tools needed to investigate, analyze, and model complex adaptive systems across a wide range of disciplines.
• Develop a new generation of leaders and advocates who champion CAS science, promoting its applications across various fields and addressing critical societal issues.
• Foster an inclusive and collaborative learning environment where diverse perspectives and approaches are valued, nurturing the intellectual growth and potential of each student.
• Establish ASU as a prominent leader in the field of CAS science, fostering research excellence, innovation, and global collaboration.

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Degree Structure:

The CAS program consists of 84 credit hours of coursework and research activities. This includes:

• Required Core: 3 credit hours in CAS 570 Fundamentals of CAS Science.
• Focus Area: Students choose either domain science or transdisciplinary bridging for 6 credits.
• Electives: 51 credits from various areas, allowing students to tailor the program to their interests.
• Research: 12 credits focused on conducting original research in the chosen field.
• Culminating Experience: 12 credits for the final dissertation.

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Outline:

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Domain Science Focus Area

Students in this area deepen their CAS understanding within a specific social science, life science, physical science, or engineering field. They are expected to make substantial contributions to their chosen domain using the perspectives and tools of CAS science.

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Transdisciplinary Bridging Focus Area

Students in this area advance their CAS understanding alongside advanced computer science and data science. This focus aims to enable them to utilize CAS as a bridge between various disciplines, applying their expertise in complex systems, data science, and IT to solve complex problems.

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Assessment:

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Assessment Methods:

• Examinations: Comprehensive and oral exams assess students' knowledge and understanding of CAS concepts, methods, and theoretical foundations.
• Dissertation Research: The dissertation is an extensive research project requiring students to demonstrate independent research abilities, analysis, and problem-solving skills in their chosen domain.
• Coursework Assessments: Regular assessments through essays, presentations, and assignments evaluate students' grasp of concepts and their application to specific topics and problems.

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Assessment Criteria:

• Depth of understanding and critical analysis of CAS theory and principles
• Ability to apply CAS methods and models effectively in research and analysis
• Communication skills through written assignments, presentations, and the dissertation defense
• Independent research skills, problem-solving, and innovation in research projects
• Overall academic achievement as evidenced in coursework, assessments, and research work.

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Teaching:

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Teaching Methods:

The CAS program utilizes a combination of teaching methods to facilitate student learning and engagement, including:

• Interactive lectures
• Seminar discussions with a strong focus on dialogue and student participation
• Project-based learning activities requiring collaboration among peers
• Individual mentorship and advising from faculty members with expertise in the student’s chosen focus area

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Faculty:

The CAS program boasts an impressive roster of dedicated and renowned faculty members from diverse disciplines, with research interests ranging from social systems to computational modeling and ecological dynamics. These faculty are actively engaged in cutting-edge research and bring their real-world expertise to the classroom, ensuring a stimulating and enriching learning environment for all students.

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Careers:

The CAS PhD program prepares graduates for diverse and impactful careers across numerous sectors:

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Sustainability:

Sustainability scientists, consultants, and policy analysts addressing environmental and societal challenges

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Social Sciences:

Researchers and policy analysts working in areas such as public health, education, and urban development.

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Life Sciences:

Computational biologists, ecological modelers, and researchers contributing to advancements in biomedicine.

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Physical Science and Engineering:

Scientists and engineers specializing in complex systems modeling and analysis within fields like climate science and materials science

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Data Science and Technology:

Professionals specializing in big data analysis and utilization of complex adaptive systems principles within the tech industry Graduates will also be equipped for careers in academia as researchers or professors, applying their expertise to further develop the field of CAS and its applications in the years to come.