Wireless Networks around us are continuously evolving to enable faster connectivity to a broader number of devices, and as a by-product, they also enable sensing of large amounts of spatio-temporal data representing an important proxy to study human mobility. These large data sources allow us to study various aspects of mobility dynamics and its influence in our social behavior. The potential applications of studying mobility dynamics can be wide-ranging. Just recently, several countries used different tools and techniques that allowed them to understand the mobility patterns of citizens at large and control the spread of COVID-19 outbreak with strategical lockdowns.
In this seminar, we will explore recent research work in human mobility with special focus on urban and network infrastructure planning as well as relationships between mobility and social networks. Furthermore, sub-topics will involve big data, statistical modeling, machine learning, complex systems and privacy.
Tentative: Depending on how large the group will be, and how many students accept to take part in an experiment, we will collect (using the Aware Framework) and analyze mobility data to see the effects COVID-19 might have had in people's mobility.
- Pre-course meeting: 4th/February/2021 15:00 @ https://bbb.rbg.tum.de/leo-5ph-f2a-l22
- Course duration: April/21 - July/21
- Weekly for the first few weeks (theoretical part)
- Bi-Weekly for the rest of the semester (papers presentation)
- Tentative: we will try an experiment, collecting mobility data to later analyze possible changes brought by lockdown.
The participants should already be prepared by an undergraduate-level course on computer networks and data analysis. Familiarity with machine learning and network theory may be beneficial, though not required.
Relevant Conferences and Journals:
- IEEE/ACM Transactions on Networking
- ACM SIGCOMM Computer Communication Review
- ACM Communications of the ACM
- ACM SIGCOMM
- ACM MOBICOM
- IEEE INFOCOM
- The Web Conference
- Nature (Human Behavior, Technical Reports, etc.)
- European Physical Journal Data Science
- Proceedings of the National Academy of Science
Learning outcomes (study goals):
The topics covered in this seminar revolve around human mobility, its causes and effects as well as possible applications in the design of better computer networks. The papers will give students the technical knowledge and understanding on the latest advancements in the field of emerging networking solutions. The participants will also learn how to critically read and discuss research papers. This will be achieved by reviewing papers individually, and actively participating in group discussions during the seminar presentations.
Detailed goals of the seminar:
- Understand why studying human mobility is important for understanding the nature of human behavior and its practical implications in resource planning.
- Explain and quantify various aspects of human mobility.
- Discuss available methods for gathering and analyzing such datasets while preserving the privacy of the studied subjects.
- Understand the importance of (independent) peer reviews.
- Present research in a concise way and within allotted time.
Teaching and learning methods:
- Written paper reviews before the presentation
- Weekly presentations during the semester
- Group discussions