Excellence Programmes

Our scientists are passionate about their research and regularly excel in international competition. Here you can find current and completed grants from the highly competitive funding lines of the European Research Council (ERC).

Current Projects


The ERC Proof of Concept project “AssemblySkills” builds on the artificial intelligence methods developed within the ERC Starting Grant “SKILLS4ROBOTS – Policy Learning of Motor Skills for Humanoid Robots”. The latter has yielded a structured, modular control architecture that has the potential to scale robot learning to more complex real-world tasks. In this modular control architecture, elemental building blocks – called movement primitives, are being adapted, sequenced or co-activated simultaneously to fulfill the robot’s tasks.

Within the Proof of Concept project “AssemblySkills”, the goal is to group these modules into a complete software package that can enable application-driven robots to learn new skills – particularly in assembly tasks. The value proposition of the project now funded by the ERC Proof of Concept grant is a cost-effective, novel machine learning system that can unlock the potential of manufacturing robots by enabling them to learn to select, adapt and sequence parametrized building blocks such as movement primitives. The approach of Professor Jan Peters’ research team is unique in the sense that it can acquire more than just a single desired trajectory as done in competing approaches, capable of save policy adaptation, requires only little data and can explain the solution to the robot operator.
Prof. Jan Peters, Ph.D.
Intelligent Autonomous Systems Group

Funding duration: 2021 – 2022
RED – Robust, Explainable Deep Networks in Computer Vision
The goal of this project is to develop methods that make artificial neural networks in computer vision, particularly so-called deep networks, more robust and more explainable. One particular aim is to increase user trust in machine learning approaches to computer vision, for example in the context of autonomous vehicles.

The project ultimately aims to create a toolbox with architectures, algorithms, and best practices for deep neural networks that enable their use in computer vision applications in which robustness is key, data is limited, and user trust is paramount.
Prof. Stefan Roth, Ph.D.
Visual Inference Lab

Funding duration: 2020 – 2025

Project Fact Sheet at CORDIS
PSOTI – Privacy-preserving Services On The Internet
The main goal of “PSOTI” is to develop privacy-preserving services for commonly used applications on the Internet like data storage, online surveys, and email. These services will provide extensive functionalities and will allow to securely and efficiently store, retrieve, search, and process data. This will allow to comply with the EU General Data Protection Regulation (GDPR) and preserve the fundamental rights to privacy and the protection of personal data.
A practical system for secure multi-party computations will be developed which can also be used for the secure processing of other sensitive data such as in the areas of genomics or machine learning. Also protocols for private search queries will be built that even hide the structure of the query and that can be used in multiple application scenarios.
Prof. Dr.-Ing. Thomas Schneider

Funding duration: 2020 – 2025

Project Fact Sheet atCORDIS

Past Research Programmes

REScala – A Programming Platform for Reactive Data-intensive Applications
REScala is a reactive language which integrates concepts from event-based and functional-reactive programming into the object-oriented world. REScala supports the development of reactive applications by fostering a functional and declarative style which complements the advantages of object-oriented design.

REScala is a Scala library for functional reactive programming on the JVM and the Web. It provides a rich API for event stream transformations and signal composition with managed consistent up-to-date state and minimal syntactic overhead. It supports concurrent and distributed programs.
Prof. Dr.-Ing. Mira Mezini
Software Technology Group

Funding duration: 2019 – 2021

Project Fact Sheet at CORDIS
SKILLS4ROBOTS – Policy Learning of Motor Skills for Humanoid Robots
The goal of SKILLS4ROBOTS is to develop an autonomous skill learning system that enables humanoid robots to acquire and improve a rich set of motor skills. This robot skill learning system will allow scaling of motor abilities up to fully anthropomorphic robots while overcoming the current limitations of skill learning systems to only few degrees of freedom. To achieve this goal, it will decompose complex motor skills into simpler elemental movements – called movement primitives – that serve as building blocks for the higher-level movement strategy and the resulting architecture will be able to address arbitrary, highly complex tasks – up to robot table tennis for a humanoid robots. Learned primitives will be superimposed, sequenced and blended. Prof. Jan Peters, Ph.D.
Intelligent Autonomous Systems Group

Funding duration: 2015 – 2021

Project information at CORDIS