Re­search pro­jects and co­op­er­a­tions in Com­puter Sci­ence

ERC Advanced Grant

• Project lead: Prof. Dr. Laurent Bartholdi (Mathematics and Computer Science)
• Funding period: 2023–2028

This project lies at the intersection of complex and symbolic dynamics, group theory, decision problems, and computation. It aims to solve important problems in each of these areas using automatic actions and relations. Finite state machines, ubiquitous in theoretical computer science, will be used to define self-similar mathematical objects and develop efficient algorithms to handle them.

ERC Advanced Grant

• Project lead: Prof. Dr. Jan Reineke (Real-Time and Embedded Systems Lab)
• Funding period: 2021–2025

Many safety critical areas of our lives are controlled by computer systems: from airbag controls in cars and landing gear on airplanes to essential infrastructure such as energy supply and telecommunications. However, a crucial aspect of computer systems, the hardware-software interface, renders the development of safe and secure applications impossible at a fundamental level. This was brought to the fore in 2018, when the Spectre and Meltdown attacks were first described. Ever since, hardware and software developers have been struggling to mitigate the resulting vulnerabilities. The EU-funded SafeSecS project is tackling this challenge with a new framework to guarantee key safety and security features at the software level on top of novel hardware-software contracts.

Go to the website of the ERC grant SafeSecS

ERC Starting Grant

• Project lead: Prof. Isabel Valera (Machine Learning)
• Funding period: 2023–2027

To date, the design of ethical machine learning (ML) algorithms has been dominated by technology owners and remains broadly criticized for strategically seeking to avoid legally enforceable restrictions. In order to foster trust in ML technologies, society demands technology designers to deeply engage all relevant stakeholders in the ML development. This ERC project aims at responding to this call with a society-aware approach to ML (SAML). Our goal is to enable the collaborative design of ML algorithms so that they are not only driven by economic interests of the technology owners but are agreed upon by all stakeholders, and ultimately, trusted by society. To this end, we aim to develop multi-party ML algorithms that explicitly account for the goals of different stakeholders—i.e., owners, those experts that design the algorithm (e.g., technology companies); consumers, those that are affected by the algorithm (e.g., users); and regulators, those experts who set the regulatory framework for their use (e.g., policymakers).

Go to the website of the ERC grant SAML

ERC Advanced Grant

• Project lead: Prof. Dr. Andreas Zeller (Software Engineering)
• Coordinator: CISPA Helmholtz-Zentrum für Informationssicherheit
• Funding period: 2023–2028

In this project, funded by the European Research Council with an Advanced Grant, Prof. Dr. Andreas Zeller and his team are developing software bots that automatically test, debug and monitor software systems – all kinds of systems, anywhere, anytime.

Go to the website of the ERC grant S3

Daimler and Benz Foundation |  Ladenburg Research Network

• Involved chair: Prof. Dr. Dominik Brodowski (Europeanization, Internationalization and Digital Transformation of Criminal Law and Criminal Procedure)
• Funding period: 2025-2027

The opportunities of modern software technologies for the legal system are being investigated in a new research network of the Daimler and Benz Foundation. The so-called ‘Ladenburg Research Network’ is focussing on large language models and their significance for the justice system. Dominik Brodowski, Professor of Criminal Law and Digitalisation at Saarland University, is also involved in the joint project.

Further informationen about TITAN