The structure of the home Informatics Complex Networks & Systems PhD program is very flexible, light on required courses, and specifically designed for interdisciplinary training via Complex Networks & Systems. The program uses an individualized qualifying exam and dissertation proposal format.
In practice, only five to six core courses (15 to 18 credit-hours) are required:
Deals with the foundations of Informatics as an interdisciplinary field. Concepts such as information, modeling, and computational thinking, as well as their impact on science and society, are presented with the relevant literature.
Surveys a broad range of research methods in the social sciences as they pertain to Informatics. It is a starting point for further study of specific human-centered research methods; *waived for students in a social science dual program.
Covers traditional and current research in CNS; focus on concepts necessary to understand research in the area, with examples from many disciplines including biology, data and sport analytics, social science, informatics, neuroscience, and economics; *waived for students in a physical or behavioral science dual program.
This course teaches the fundamental theories, algorithms, and key applications of network science across social and biological systems. Python is the main programming language.
Presents the history, methodology and impact of complex systems. It covers key literature as well as recent advances in the field, focusing on interdisciplinary problems and the discovery of general principles of organization.
Focuses on late-breaking research and leads students to start novel projects at the frontiers of the field. It trains students to think like a CNS researcher and apply methods to their research goals with the completion of a small publishable project.
*The syllabus of the I501/I502 series extensively addresses professional development in interdisciplinary STEM research, from both the quantitative and human-centered perspectives, perfecting skills necessary for both academic and professional careers.
The CNS track of the Informatics PhD program also offers many elective courses in the field, allowing trainees to gain specific methodological expertise. Examples of such courses are:
I-585 - Biologically-inspired computing (Rocha)
I-590 - Collective Intelligence (Bollen)
I-590 - Data Visualization (Ahn)
I-590 - Mathematical Modelling of Social Dynamics (Fortunato)
I-590 - Mining The Social Web (Menczer)
I-590 - Performance Analytics (Radicchi)
CSCI-657 - Computer Vision (Crandall)
Q-580 - Introduction To Dynamical Systems (Beer)
S-637/E-583 - Information Visualization (Börner)
Interdisciplinary Training in Complex Networks and Systems resources and social media channels