Algorithms for Temporal Graphs (completed)

Starting Date: Summer 2022
Prerequisites: Algorithms and Complexity
Will results be assigned to University: No

The project will be co-supervised with Argyris Deligkas.

The focus of the project is to study and optimize real-life networks that change over time. Some prominent examples of such networks include logistics schedules, public transportation systems, electricity-demand over power grids, information flows, and virus spreading. We plan to study this type of problems through the lens of temporal graphs; a well-established model that can naturally capture the objectives and the constraints that arise from the above-mentioned dynamically evolving networks.

Our main goal is to identify patterns in the temporal graphs that emerge from real life applications that can be exploited to obtain efficient algorithms, or rule out existence of such algorithms.

We will explain to you the basics of Temporal Graphs and help you to understand the solution concepts we will study. Depending on the outcome of the project, we can submit our findings to a conference related Theoretical Computer Science or Artificial Intelligence.