S³ 2026

Human activities have substantially altered ecosystems. This means that all kinds of organisms now have to cope with different stressors, such as global warming, pollution, invasive species, and habitat destruction. We already know that such alterations cause a loss of biodiversity, bringing countless species to the verge of extinction. To stop this, we need to better understand how organisms and ecosystems react to different stressors. While some stressors are well researched, others still raise many questions for scientists.

In this project, we take on the role of environmental protection researchers. Our goal is to gather more knowledge about lesser-understood environmental stressors, such as light pollution. Humans use light to navigate through darkness, but we do not yet fully understand how artificial light at night interferes with our co-inhabitants on Earth. Light is a very important environmental cue because it sets internal clocks and coordinates the daily activity and behaviour of all organisms. In this project, we aim to assess pollution levels in the city and compare them to those in a less polluted natural ecosystem. First, we will identify light sources and other pollutants and collect field data to see how organisms have reacted and adapted to these stressors. We will then analyse samples using ecological and laboratory methods and evaluate our results. Ultimately, we will discuss different conservation methods and take on the role of city planners to design more ecosystem-friendly lighting strategies.

The brain (you have probably already heard of it) is a very important organ. So important that your body decides to protect it with a whole armour of bone. Its job is to communicate with your tissues, in a complex language that the cells understand. And what if we were able to understand it too? Translating the language of the brain would allow us to do plenty of things, like understand the mechanisms behind cognition, mental health, decision making, movement, and even use the brain language to control external devices. We could then use this knowledge to develop psychological treatments, cure brain disease, and engineer complex, limb-like prostheses.

During this project, we will dive in the broad discipline of neuroscience, learning about the anatomy and physiology of the brain, an organ that has been a big question mark for a lot of the human history. We will then learn the technological methods to acquire brain signals and to transform them in information we can use to modulate simple commands. Finally, we will build a simple game that shows what we have learnt about the brain and how it works, and use real time acquisition of brain waves to control it. This project will show how we are able to understand the brain's language, and utilize it in outer machines.

Every day, we make decisions without knowing what the outcome will be – from choosing how to spend our money to planning our next move in a game. In many real-world situations, such as financial markets and AI systems, results depend on chance, incomplete information, and the actions of others. Understanding how to evaluate a decision, while weighing its risk, is becoming increasingly important in a world shaped by fast-moving data, predictive algorithms, and strategic thinking. These ideas are not only relevant to investors and data scientists, but also appear in games like chess, where players must make the best possible move with limited information while anticipating their opponent’s response.

In this project, you will explore how decisions are made under uncertainty and what influences our choices. You will discover how to assess potential outcomes using tools such as probability, decision trees, and payoff matrices. Through a series of interactive games and challenges, you will test different approaches and see how small decisions can have significant consequences. You will also step into the role of a trader in a market simulation, buying and selling as prices shift in response to the actions of others, just like real investors. Along the way, you will uncover why humans often make surprising choices, why intuition sometimes clashes with mathematics, and how thinking strategically can help you adapt and thrive in fast-paced, dynamic environments!

We live in a time where Machine Learning is getting more and more important, with AI models being used for an increasing number of tasks, such as sorting through job applications or identifying academic fraud. Therefore, it is important to make sure that computers make good decisions that do not unfairly discriminate anyone. For example, nobody wants their university application denied because of their race or their gender. But what exactly does it mean to make a fair decision? How can we teach that to an algorithm? And how do algorithms “decide” or “learn” something, anyway?

Those are the questions we will attempt to answer in this project! To that end, we will look at different definitions of fairness, how to express them so that a computer can understand them and evaluate both how accurate and how fair or unfair some machine learning models are. You will learn how to evaluate algorithms and we will discuss how different evaluation methods are in conflict with each other. We will also consider what kind of role datasets and potential data bias play for fairness in machine learning. And we will be working on how to make machine learning models more fair. You will learn the basic theory behind a few standard machine learning models and train and test models of your own. Our work will focus mainly on classification models – which sort data samples into pre-defined classes – and we will mainly use smaller models rather than deep neural networks. We will work with the programming language Python, but no previous experience in coding is required.

This year's Summer School of Science will continue the tradition of hosting a project in collaboration with the Department of Earth and Planetary Sciences at ETH Zürich. The project will explore cutting-edge topics in geophysics and climate change.

Full details will be announced soon. In the meantime, take a look a ETH Zürich collaboration projects from 2025 and 2024 to get a sense of what's coming.