ERC Starting Grant | Prof. Jan Peters
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.
Funding duration: 2015 – 2020
Prof. Jan Peters, Ph.D.,
ERC Consolidator Grant | Prof. Patrick Eugster
LiveSoft investigates static techniques to verify a subset of relevant and failure-prone aspects of distributed software interaction between components in a way which is lightweight and can be integrated with compilation. A main challenge is to support different system and failure models including emerging hardware trends such as hardware transactional memory and non-volatile memory rather than hardwiring specific notions of (a)synchrony and failures.
Funding duration: 2014 – 2019
Prof. Patrick Eugster, PhD,
ERC Starting Grant | Prof. Stefan Roth
This ERC-funded project is concerned with the joint estimation of several scene attributes from one or more images, with the aim of leveraging their dependencies. The project covers aspects of modeling, learning and inference (in) such models.
Funding duration: 2013 – 2018
Prof. Stefan Roth, PhD,
ERC Advanced Grant | Prof. Mira Mezini
PACE will deliver first-class linguistic abstractions for expressing sophisticated correlations between data/events to be used as primitives to express high-level functionality. Armed with them, programmers will be relieved from micromanaging data/events and can turn their attention to what the cloud has to offer. Applications become easier to understand, maintain, evolve and more amenable to automated reasoning and sophisticated optimizations. PACE will also deliver language concepts for large-scale modularity, extensibility, and adaptability for capturing highly polymorphic software services.
Funding duration: 2013 – 2018
Prof. Dr.-Ing. Mira Mezini,
Emmy Noether Research Group | Prof. Michael Pradel
The ConcSys project develops program analyses and software systems that help programmers to make complex, concurrent systems significantly more reliable and efficient than they are today. The ConcSys project develops program analyses and software systems that help ordinary programmers to make complex, concurrent systems significantly more reliable and efficient than they are today. To achieve this goal, the project combines scalable static analysis, precise dynamic analysis, and automatic test generation. This combination is beneficial because dynamic analysis addresses the inherent imprecision of scalable static analysis, while automatic test generation provides a driver for dynamically analyzing a program. To underpin our work, we develop a framework for evaluating our techniques in a rigorous and comparable way. The ConcSys project focuses on approaches that are applicable to large, real-world systems with millions of lines of code and therefore, will contribute towards making tomorrow's software systems reliable and efficient.
The project is funded as an Emmy Noether project by the German Research foundation (DFG) for a duration of 5 years (2014 – 2019).
Prof. Dr. sc. Michael Pradel
Emmy Noether Research Group | Prof. Sebastian Faust
Cryptographic algorithms and protocols are widely implemented in practice and guarantee data confidentiality and integrity. They help to prevent fraud in, e.g., electronic payment systems, and play a fundamental role in daily life. Modern cryptography analyzes the security of cryptographic algorithms using a mathematical framework based on formal security definitions and a proof-driven security analysis.
To this end, an adversarial model is defined that specifies the capabilities of an attacker and describes the environment in which cryptographic algorithms are executed. The most prominent security model is the black-box model, where cryptographic algorithms are assumed to be executed in a highly idealized environment.Unfortunately, many examples illustrate that the idealized assumptions made in the black-box model often cease to hold when adversaries attack cryptographic implementations. This gap between idealized security models and the practical security of cryptographic implementations is in particular shown by the following shortcomings:
- A) Bad randomness
- B) Side-channel attacks
- C) Faulty and malicious implementations
The expected outcome of the project are new cryptographic techniques and security models for developing the next generation of cryptographic implementations. To achieve these goals, we will extend the black-box security analysis to the implementation-level by developing methods for mitigating the problem of bad randomness (shortcoming A), and designing sound countermeasures that can protect against implementation attacks (shortcoming B). We will also address issues of the implementation process itself by designing verification tools and providing defence mechanisms against malicious implementors (shortcoming B).
Funding: since 2015
Prof. Dr. Sebastian Faust
Excellence Initiative | Graduate School Computational Engineering
(Excellence Initiative of the German Federal Republic and the Federal States)
The Graduate School of Excellence Computational Engineering (CE) at the Technische Universität (TU) Darmstadt has been recognized as a center for top-level research and scientific excellence by the highly competitive 'Excellence Initiative' of the German Federal and State Governments. The Graduate School enables PhD students to develop their scientific skills in a focused way, and to cooperate under optimal conditions in a highly stimulating interdisciplinary environment.
Past Research Programmes
Heisenberg-Professorship | Prof. Marc Fischlin
The purpose of the Heisenberg-Program is to “provide outstanding researchers who fulfil the requirements for appointment to a long-term professorship with the opportunity to prepare for a leading position in science and research and to use the time to work on an advanced research topic…“ (DFG)
The goal of the research project “Scrutinizing Black-Box Separations in (Quantum) Cryptography” (BBQCrypt)” is to burst open the doors to new design methods for cryptographic protocols, overcoming widely-accepted limitations due to black-box separation results. Non-black-box results are at a very early stage of scrutiny, and black-box separations are still viewed as strong evidence that some limitations are inherent, especially in the area of practical cryptographic constructions. This confined way of thinking, however, forecloses ambitious efforts to find solutions beyond the current state of knowledge. The project should therefore help to overcome this narrow view and to break new ground for cryptographic tools and constructions.
Prof. Dr. Marc Fischlin,
Lichtenberg-Professorship funded by Volkswagen-Stiftung | Prof. Iryna Gurevych
Prof. Dr. Iryna Gurevych
Ubiquitous Knowledge Processing (UKP Lab)
Emmy Noether Research Group | Prof. Eric Bodden
Funding: DFG, since 2012
Professor Dr. Eric Bodden
Universität Paderborn, Heinz Nixdorf Institut
Emmy Noether Research Group | Prof. Marc Fischlin
Emmy Noether Research Group | Prof. Michael Goesele
Funding: DFG, 2009 – 2016