PhD Network Science

Upon program completion, graduates will demonstrate an understanding of foundational network science concepts. You will be able to:

• Define and interpret—both mathematically and conceptually—network metrics, network properties, and network growth. This includes centrality and clustering; robustness and scale-free; preferential attachment and percolation, respectively.
• Identify, generate, analyze, and compare different network models in terms of their network properties and processes. For example, using real-world examples of bi-partite, hierarchical, scale-free multiplex, or multi-dimensional networks to generate and compare network models in terms of degree distribution, dynamics, and clustering behaviors.
• Understand mathematics and theories of network spreading models and how to apply these in a meaningful way across domains. For example, using the set of epidemiological models to calculate epidemic thresholds, predict spreading behaviors, and develop immunization strategies, as well as understanding different features and constraints when the infectious agent is biological, informational, or behavioral.
• Exhibit competency in core network data mining techniques from real-world datasets to networks.
• Develop basic data visualization techniques to present network findings in a compelling and accurate way.
• Learn fundamentals of network-based computer programming. This includes acquiring and handling large data sets and cloud computing basics, as well as building and analyzing networks using control structures, data structures, and algorithms.
• Attain a critical mass of understanding of a substantive domain complementary to network science. Common applications include epidemiology, brain science, political science, ecology, organizations, and data mining.
• Work as a member of a collaborative research team. Students learn techniques that enable them to contribute technically to multi-disciplinary teams, conferences, and articles.
• Identify network-based research questions and lead independent projects in a major field of study.
• Convey network science concepts, methods, and results both verbally and in writing. Students gain experience and training in communication in multiple venues, including presenting their work for scientific conferences, industry partners, community-based organizations, and granting agencies.
• Write empirical and review papers for publication in scientific journals. Students typically have the opportunity to independently submit and revise a manuscript for publication, as well as contribute to major grant proposals to NSF, DOD, or other large funding agencies.
• Gain knowledge of current network science research with the ability to articulate and discuss open questions in the field. Through journal clubs and various speaker series, students regularly engage in deep exploration of both foundational discoveries and current advances in the field—making them well informed and adept to discuss major tensions and challenges in the field.