June 8 to June 19, 2026 | Rotterdam, the Netherlands
ODISSEI-SICSS is split into two phases. During the first week, the participants will be introduced to ODISSEI and taught machine learning in Python. This will be primarily done through a course run by the eScience center. In the second week of the summer school, participants will be able to make full use of the ODISSEI infrastructure, during which they will be put into teams and challenged to work on research projects. Each team will be provided with access to the secure environment SANE where they will be able to work with FIRMBACKBONE data (containing detailed information on Dutch companies), sensitive LISS panel data, and environmental data from Exposome. Specifically for FIRMBACKBONE, researchers will get access to the corporate trade register, employment surveys, financial data, emission data, and indicators derived from websites.
ODISSEI provides access to a treasure trove of data which can help us predict important outcomes. The teams will compete to develop effective predictive models to answer innovative research questions. This challenge will help participants get a more hands-on experience of computational social science research with some of the most advanced data infrastructure available.
At the end of most days of the summer school, there will be a guest speaker who will present their work or a general topic in computational social science to the participants. These talks will last 20-30 mins with 15-20 mins of Q&A. Slides will be added on the ODISSEI Zenodo Community; other material will be shared via GitHub.
All course sessions will take place in the Polak Building on the Erasmus Campus Woudestein, Burgemeester Oudlaan 50, Rotterdam. You can find information here and download the campus map here. Throughout the summer school, ODISSEI will organize various social events. Read more about those in the timetable below. Each day will have three breaks. A coffee break in the morning, lunch at 12:00, and another coffee break in the afternoon.
10:00 - 12:00: Introducing ODISSEI and Computational Social Science. Speaker: Tom Emery
12:00 - 13:00: Lunch break
13:00 - 14:15: Using the SANE environment. Speaker: Angelica Maineri and Tom Emery
14:15 - 14:30: Coffee break
14:30 - 16:00: Introduction to FIRMBACKBONE, LISS and Exposome. Speaker: Tom Emery
16:00 - 16:15: Coffee break
16:15 - 17:00: Research Ideas Speed Dating
Social Event (17:00 - 19:00): Opening Drinks at Paviljoen, EUR Woudestein campus
Location: Room:3.09, Polak building
09:30 - 12:00: Handling Geospatial Data. Speaker: Tom Emery
12:00 - 13:00: Lunch break
13:00 - 16:00: Causal Geospatial Analysis. Speaker: Javier Garcia Bernardo
16:00 - 17:00: Guest lecture by Elizaveta Sivak on the PreFer challenge
Location: Room:3.09, Polak building
09:00: Welcome and icebreaker
09:15: Introduction to machine learning
10:00: Break
10:10: Tabular data exploration
11:00: Break
11:10: Fitting a scikit-learn model on numerical data
12:00 - 13:00: Lunch break
13:00: Fitting a scikit-learn model on numerical data
14:00: Break
14:10: Fitting a scikit-learn model on numerical data
15:00: Break
15:10: Cross-validation
15:45: Wrap-up
16:00 - 17:00: Guest lecture: Ana Petrovic on Neighbourhood Analysis
Location: Room:3.09, Polak building
09:00: Welcome and recap
09:15: Handling categorical data
10:00: Break
10:10 Using numerical and categorical variables together
11:00: Break
11:10: Intuitions on decision trees
11:30: Overfitting and underfitting
12:00 - 13:00: Lunch break
13:00: Validation and learning curves
13:30: Advanced topics
14:00: Break
14:10: Try out learned skills on new dataset
15:00 - 16:00: Guest lecture by Ana Macanovic on Text Analysis
16:10: Concluding remarks
16:45: Wrap-up & Post-workshop Survey
Social Event (17:30 - 20:00): Drinks at De Gele Kanarie
Location: Room:3.09, Polak building
09:30 - 12:30: LLM fundamentals for Social Science Research. Speaker: Qixiang Fang
12:30 - 13:30: Lunch break
13:30 - 15:00: Inference with LLM Annotations. Speaker: Qixiang Fang
Location: Room:3.14, Polak building
10:00 - 11:00: Introducing the Data Challenge
13:00 - 17:00: Research project
12:00 - 13:00: Lunch break
Location: Room:3.09, Polak building
09:00 - 17:00 Research project
12:00 - 13:00: Lunch break
Location: Room:3.09, Polak building
09:00 - 12:00 Research project
12:00 - 13:00: Lunch break
13:00 - 15:30 Research project
15:30 - 17:00 Ethics Workshop. Speaker: Chirag Arora
Location: Room:3.09, Polak building
09:00 - 17:00 Research project
12:00 - 13:00: Lunch break
Closing dinner (18:00 - 21:00 ) at Tasca Plein Oost
Location: Room:3.09, Polak building
10:00 - 12:30 Final Presentations
12:30 - 13:30: Lunch & Closing - Participants are free to leave from 12:30
Location: Room:3.09, Polak building
You can host a partner location of the Summer Institutes of Computational Social Science (SICSS) at your university, company, NGO, or government agency.