Instructor: Victor M. Preciado, preciado [at] seas.upenn.edu
Meeting Info: MW 4:30-6:00 PM in Towne 307

Course Description:
Networks are ubiquitous in our modern society: Social and economic networks, natural networks (e.g., in biology), infrastructure networks (e.g., communications, the internet, transportation, energy), and networked decision and control systems (e.g., sensor networks, autonomous multiagent systems). This course deals with tools, methods, and algorithms for analysis and design of networked dynamical systems. The object of study in this research seminar are large collection of dynamical systems that are spatially interconnected to form a collective task or achieve a global behavior using local interactions. The purpose of this course is to build a mathematical foundation for study of such systems by exploring the interplay of control theory, distributed optimization, dynamical systems, and graph theory.


This course is a research seminar and requires a lot of independent work. Although we will have a few traditional lectures covering the fundamentals of network structure and dynamics (see Schedule), students will need to be able to critically read and analyze research papers across various disciplines (see Readings). Furthermore,  as part of the requirements of the course, you need to complete a project on a topic of your choice, related to the class material. We encourage you to work in groups of 2-3 people. 

Grading will be based on the following items:
  • Class participation (10%): Involvements in presentations and discussions.
  • Research Literature Review (30%) and Presentation (20%): Read and prepare a review presentation on 2-3 research papers on a theoretical or application area related to the subject of the course. This involves deep understanding of and critically evaluating the papers (a list of suggested papers can be found in Readings, although papers proposed by the students are also welcome).
  • Research Project Report (40%)There is a lot of flexibility on the choice of the topic, as long as it overlaps with issues and methods covered in this class. We will be happy to discuss candidate topics with you and provide pointers to the literature. (You can read more about the project specifications in here).

Linear systems (ESE 500), Linear algebra (Math 412 or equivalent), and Probability are required. Those without this background should consult the instructor.