Introduction to the topic
This project investigates human mobility patterns by analyzing diverse real-world datasets. The main goal is to identify and describe how individuals travel and interact across different spaces in their daily lives.
Understanding how humans travel and their mobility patterns can help designing solutions to real-world challenges. For example, the findings can help optimize transportation systems and road network design to reduce congestion and improve efficiency. They can enhance ride-sharing services by predicting demands and suggesting better routes, and improve mobile technologies, such as activity recognition (e.g. identifying when a person is walking or driving) and data pre-fetching (e.g., pre-loading data to ensure smooth user experiences of e.g. maps or streaming services).
Mobility patterns can also provide insights into social behaviors, such as how people gather and interact, while also identifying potential privacy risks with mobility data sharing, like the potential for re-identifying individuals in anonymized datasets.
Project details
This project is organized in three tracks: (1) analyzing individuals’ travel patterns and behaviors, (2) identifying common travel routes through complex network modeling, and (3) assessing the risk of identity re-identification in anonymized mobility data.
Research Assistants (RAs) will engage in tasks such as conducting literature reviews and contributing to the design and execution of research plans. Your responsibilities will include developing and implementing methods and algorithms, as well as performing data pre-processing, analysis, and interpretation.
The scope of your work is flexible and can be adjusted to align with your specific interests and expertise. You will gain insight into the field of human mobility research and learn how to design and structure your own research, while being introduced to techniques and methodologies from fields such as Natural Language Processing, Complex Networks, and Data Privacy. Through the research track and dataset(s) you choose to work with, you will gain hands-on experience in analyzing, interpreting, and presenting large datasets. Additionally, you will develop your academic writing skills and enhance your ability to effectively communicate complex research findings
Research Assistantship Hours
You will spend 180 hours directly engaged in research, together with 20 hours in co-curricular activities, during your RAship.
Field Studies: Culture & Language
As a co-curricular complement to your summer research, you will meet every Wednesday, together with faculty from the DIS European Humanities program, for a 6-week introduction to culture and language in Copenhagen.
Prerequisites
One year of computer science at university level and a course in algorithms and data structures.
Recommended experience
Decent knowledge of Python programming language is an advantage.
Additional application required
You will need to submit an additional research application through the Student Registration in order to enroll in this course.
Before you submit your research application, you must already be admitted to DIS.
All application materials must be submitted by 23:59 Central European Time on March 15.
Faculty
Panagiota Katsikouli
FacultyPh.D. in Informatics, University of Edinburgh (2018). Currently lecturing as Faculty Member at the Open Institute of Technology (2023-present) and involved in Teaching and Research at the University of Copenhagen (2020–present). Previous experience as post-doctoral Researcher at the Technical University of Denmark (2019-2020), University College of Dublin (2019), and INRIA Lyon (2018-2019). Teaching and Research. With DIS since 2023.
More information about your Research Assistantship
Learn more about the Labs, Research, and Practicums Summer Session.