Dual CNS PhD

Interdisciplinary Dual PhD Program

Informatics and computer science grew out of the desire to find common principles of organization in living, cognitive, and social systems. The mid-XX century Cybernetics group of Wiener, Shannon, Von Neumann, Turing and others aimed to invent digital computers precisely to uncover general principles of organization. Weaver makes this clear in his seminal 1948 paper that pushes science to study the common principles of organized complexity across nature and society with computers. This spawns the Systems Movement, which later becomes the field of Complex Systems. Complexity has since then been intimately linked to informatics, and the computer has become the laboratory of the complex systems scientist.

CNS-NRT Animated LogoThe field started with collaboration between mathematicians, physicists, biologists, neuroscientists and sociologists (e.g. McCulloch, Rosenblueth, Mead, von Neumann, Wiener, etc.) and it remains committed to an interdisciplinary agenda, successfully translating theory to solve problems in social sciences, public health, physics, biology, neuroscience, and in a long and growing list of other fruitful examples. Common to all these disciplines, and more, since it is useful to describe Interactions in the, biochemical, neural, environmental, technological, knowledge and social spaces we live in, is the paradigmatic and most successful general principle of complexity: the network.

From this backdrop comes the vision that understanding specific complex networked systems is key to solving some of the most vexing problems confronting humankind. These range from discovering how thoughts and behaviors arise from dynamic brain connections, to detecting and preventing the spread of misinformation, stigma, or unhealthy behaviors across a population. Modeling network interactions among variables operating at multiple scales is an essential capability for effective interventions in complex systems− human well-being, for instance, as depicted at the various, interacting levels from genes to the social.

This interdisciplinary training program in network science and complex systems leads to a dual PhD degree whereby all students are trained in our Complex Networks and Systems PhD program, in addition to a second PhD program such as Cognitive Science, Political Science, Psychological & Brain Sciences, Sociology, and others. The training activity is also based on hands-on, team-centered and data-enabled science as described below.


Our goal is to train scientists who can easily combine two or more dimensions of science and establish the necessary team culture for solving interdisciplinary problems.

This NRT will implement new and innovative interdisciplinary training and research to push CNS methodologies from theory sidelines into a central role in natural and social sciences laboratories and practices.

Goal 1: Dual Research Proficiency

    • Computational and mathematical training to infer, analyze, and model complex networks and systems;
    • Experimental and methodological training from domain-specific natural and social sciences;

Goal 2: Collaborative Skill Development

    • Early integration into problem-driven, interdisciplinary projects with teams of leading scientists at IUNI who collaborate to study multi-level phenomena;
    • Publish research with impact in more than one discipline;

Goal 3: Workforce Development

    • Recruit, train and place in top research institutions and companies a cohort of students who though diverse in their starting disciplines, become able to thrive in the integrated team culture that can solve problems which simultaneously require proficiency in general methods and deep domain specificity;
    • Increase the participation of underrepresented groups in STEM science;

Goal 4: Interdisciplinary Training Model

    • Increase the institutional capacity of Indiana University for interdisciplinary training and research using CNS, computational, and data science;
    • Systematically evaluate our success in meeting these objectives and continually adjust the components of the program in response to those evaluations;
    • Project the institutional channels created between the SICE and the CoAS, mediated by team science at IUNI, as a model training program for transcending disciplinary boundaries elsewhere.