Research Assistant: Agenda of Alternative Political Movements in Europe and Their Transatlantic Impact

Introduction to the topic

Are you curious about how people move through cities – or even across countries – and how we can use data science to better understand these patterns? Do you wonder how individuals form communities, friendships, or social structures? Would you like to explore the impact of major events, like the COVID-19 pandemic, on public transportation and daily habits using real-world datasets?

If any of this sounds exciting to you, and you have at least a basic working knowledge of Python (a programming language for data analysis), then this research project might be a great fit!

Project details

In this research project, you will explore how humans move, interact, and adapt through the lens of data science. You’ll learn how to apply data science tools to real datasets, uncover patterns, create compelling visualizations, and potentially predict future behaviors.
Together, we’ll define a project based on your interests, whether you’re drawn to mobility, social networks, or large-scale behavior changes. You’ll gain hands-on experience with real-world data, conduct research using academic methods, and learn how to communicate your findings effectively.

You will gain hands-on experience applying Python-based tools (e.g., pandas, seaborn, network analysis libraries) to real datasets and learn how to transform raw data into meaningful insights.

If you are interested in human mobility, you might investigate how individuals travel across cities or countries, what drives people to explore new places, how public transportation changes during disruptions, or what privacy risks arise from location data. Mobility datasets come from mobile apps, sensors, GPS devices, and even social media.

Humans are inherently social – we form groups, communities, and friendships, often influenced by both choice and chance. If you are interested in human relationships and social behavior, we can model and analyze how relationships form and evolve with tools from graph theory and complex networks. Understanding these connections has fascinated researchers in sociology, anthropology, and computer science.

You will define a research question that aligns with your interests. You may contribute to ongoing work or develop an independent mini project. Typical research tasks include conducting literature reviews, designing small experiments, preprocessing and analyzing data, building simple models, and communicating your findings through presentations and reports.

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.

Faculty

Panagiota Katsikouli

Faculty

Ph.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.