Mobility in Humans and Animals: A Data Exploration (SoSe 2026)

P Klamser, A Ibrahim

Opal: Link here.

Time (Lecture): Monday, 5. DS
Time (Exercise): Thursday, 6. DS

Module: BIO-MA-AQUA1, BIO-MBBT-30Q01

Language: English

Assessment: Project Presentation

Description:

This course offers an overview on movement and mobility in animals and humans from a data-driven perspective. It will cover micro- to macroscopic movement from animals and humans, collective decision making during movement processes and transport networks. The course is strongly coupled to datasets, the lectures will prepare the background, both theoretically and method wise. In the exercise the students will analyze the datasets in prepared jupyter-notebooks.

At the middle of the semester the students select a dataset and a research question, which will be presented in the last part of the semester.

No preliminary programming knowledge is necessary, all will be communicated during lecture and exercises.

The course touches an interdisciplinary field:

  • Network theory
  • Data representation
  • Random Walk, Markov Networks
  • Human mobility models (gravity, radiation)
  • Animal behavior
  • Programming skills: Python, GitHub, data-analysis
mobility animal behavior human mobility data analysis networks
Pascal Klamser
Pascal Klamser
PostDoc

My research interests include human mobility, collective animal behavior, evolution, phase transitions, disease and opinion dynamics on networks.

Abdullahi Ibrahim
Abdullahi Ibrahim
PostDoc

Abdullahi is a postdoc in SynoSys.PC. He has worked on interdisciplinary projects such as time-series prediction with ML, community detection in networks, and flows in multimodal transport networks. He is currently exploring causal inference in time series using machine learning techniques.