Advanced Topics in Information Systems for Sustainable Society (M. Sc.)
Advanced Topics in Information Systems for Sustainable Society (ATIS3) - offered by the IS3 - covers the use of information systems and quantitative decision-making under uncertainty in two vibrant areas: Sustainable smart energy markets and sustainable urban mobility. Complementing courses such as Data Science and Machine Learning, and Analytics and Applications, the course focuses especially on the operations management (OM) perspective and OM tools, such as mathematical optimization.
You will learn how energy systems change due to renewable energies and how innovative mobility systems can reduce the carbon footprint of future transportation. Within these domains, you will learn to apply optimization techniques to answer important questions, for instance: How to set dynamic prices for the energy supplier so that its customers charge their electric vehicles in a beneficial way? How to schedule the production of power plants in presence of renewable energy sources? Where to place charging stations in different parts of the city?
Energy and mobility systems exhibit inherent uncertainty. For instance, solar panels only produce energy in sunny conditions. Managing risks associated with this uncertainty is a growingly important area of management, not only in the two vibrant domains of energy and mobility (but also in finance, health care, marketing, supply chain management, etc.). You will learn how to use data-scientific methods to create scenarios that represent potential states of the future. Based on these scenarios, the stochastic optimization methods you will work with help you to find the best line of action - either in the worst case or in expectation.
While the presented techniques are advanced, we do not expect pre-existing knowledge in any of the aforementioned areas. A basic interest in quantitative and mathematical methods is sufficient. After several lecture blocks to jump-start your skillset, we will work hands-on on different problem sets from the energy and mobility domains. These use cases could also be an inspiration for potential research during your master thesis.
The grading of the course is based on an individual and a group project (equal weights). There is no exam. During both projects, you are expected to work on hands-on projects that reflect your learnings throughout the semester. Further, you show your ability to persuasively report findings in written and oral form.
We are looking forward to a highly interesting semester of Advanced Topics in Information Systems for Sustainable Society, what about you?