Seminar - Internet of People: Connectivity, Mobility and Privacy (2019)
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. 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.
Slides summarizing the content of this seminar, can be found in this link.
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
- 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. 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. Students will also have the opportunity to advance their soft skills through presentation and session moderation. Presentations will involve learning to not only stay within time limits but also to appreciate the Q/A session.
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 (40% of final grade)
- Weekly presentations during the semester (50% of final grade)
- Group discussions (10% of final grade)
Each participant covers a topic area by presenting 1-2 relevant papers during the seminar. See [a] for some examples of student presentations. To ensure everybody has read the papers, the participants are required to hand in a review of the presented papers via HOTCRP [b] following the provided review template. The answers to the review forms should be brief and concise. See [c, d] for exemplary paper reviews. Paper allocations will be done on a best-effort basis, based on preferences (favourite 2-3 topics) solicited over email during the semester. A topic will be randomly assigned if no preference is sent. The first seminar course slot (TBD) will be used to set the agenda for the seminar.
S. Keshav. “How to read a paper” ACM SIGCOMM Computer Communication Review, July 2007
William G. Griswold, “How to Read an Engineering Research Paper” cseweb.ucsd.edu/~wgg/CSE210/howtoread.html
Graham Cormode. 2009. “How NOT to review a paper: the tools and techniques of the adversarial reviewer.” SIGMOD Rec. 37, 4 (March 2009), 100-104. dx.doi.org/10.1145/1519103.1519122
J Smith. "The Task of the Referee" doi.org/10.1109/2.55470
Dagstuhl Seminar 17412, “Internet of People” www.dagstuhl.de/en/program/calendar/semhp/
Leonardo Tonetto <tonetto at in tum de>
Vaibhav Bajpai <bajpaiv at in tum de>