A Scientific Feat: Two ERC Grants in a Row


ERC Starting Grant holders Tom Lüdde and Bastian Leibe to receive Consolidator Grants

  Two men in front of Uniklinik RWTH Aachen Copyright: © Peter Winandy Delighted with their second ERC Grant: Professor Bastian Leibe and Professor Tom Lüdde

Professor Tom Lüdde was one of the first to benefit from the international grant scheme: In 2007, the European Research Council introduced its new research funding program to support outstanding scientists. The so-called ERC Grants were established to fund visionary fundamental research projects. Lüdde took this opportunity and wrote a research funding proposal – the first of his career. Only three percent of all applications were successful, including that of Tom Lüdde from the RWTH Chair of Internal Medicine with a focus on Gastroenterology and Metabolic Disorders. Thus he received a so-called Starting Grant. Now he has accomplished another major academic feat by receiving yet another ERC grant – this time a Consolidator Grant.

Fortunately for RWTH, he is not the only one to accomplish this feat: Professor Bastian Leibe from RWTH’s Computer Vision Group is the second Starting Grant recipient now to receive a Consolidator Grant. At RWTH, the only other researcher to have achieved this is Professors Magnus Rueping from the Institute of Organic Chemistry. “This is an outstanding achievement,” says Professor Rudolf Mathar, RWTH’s Vice-Rector for Research and Structure. “ERC grants are important indicators of our University’s performance.”

There are three types of ERC grant: Starting, Consolidator, and Advanced Grants; eligibility depends on the applicant researcher’s level of experience. It is quite exceptional to receive two ERC grants in a row, and so Bastian Leibe and Tom Lüdde were delighted to receive the good news: “I was overjoyed,” says Lüdde about the moment he received the approval. Right away, both researchers met up with their teams to celebrate their success.

Lüdde and his group at Uniklinik RWTH Aachen are concerned with molecular mechanisms that regulate the development of liver cancer based on fatty liver disease. Fatty liver disease is the most prevalent form liver disease in western industrial nations. An unhealthy lifestyle and obesity are among the root causes of the disease, but genetic and environmental factors may also play an important role. It is less know, however, that some patients have a larger risk of developing liver cancer. The working group succeeded in demonstrating that different stress factors, such as fatty degeneration, may induce liver cells to die in a “controlled” manner.

All cells in the human body are equipped with such “suicide programs,“ which can trigger different kinds of reactions in the surrounding liver or immune cells. Supported by the ERC grant, Lüdde now seeks to investigate which key molecules in liver cells are responsible for cell death through fatty degeneration and which signaling cues are being emitted by the dying liver cell that cause inflammation and cellular growth of other cells, which provides the basis for the development of cancer.

The aim is to be able better to determine which patients with fatty liver disease have a high risk of cancer and to develop medication that slows down or even stops this process. “It is an ambitious project – the ultimate goal is to develop a therapy up to the point where it is ready for clinical trials,” explains Lüdde. The support from the ERC is extremely valuable for his research activities. Already the first grant has given him “the freedom to reach the goals we have set ourselves.”

Progress Through Deep Learning

Vision is the most important sense with which humans perceive their environment. Today, it is highly important for technical systems such as self-driving cars to analyze camera input so as to achieve a similarly comprehensive understanding of visual scenery. Computer Vision, the field of research which seeks to provide solutions to problems like this, has made tremendous advances in recent years due to the use of “deep learning” methodologies.

Current deep learning approaches to visual scene comprehension, however, do not sufficiently integrate the 3D structure of the environment. The aim of Bastian Leibe’s project “DeeVise – Deep Learning for 3D Visual Scene Understanding” is to overcome this shortcoming and to equip deep learning approaches with an “understanding” of what it means to move about in a dynamically changing three-dimensional world.

Another objective of the project is to develop more scalable learning approaches that are capable of autonomously learning from video data and thus do not require large sets of training data provided by humans. The results of the project are expected to make important contributions to automated driving and mobile robotics. As Leibe concludes, “We have exciting ideas and we are convinced that we can achieve something great.”

Bastian Leibe

Bastian Leibe, 43, studied computer science at Stuttgart University and at the Georgia Institute of Technology. He earned his doctorate from ETH Zürich. In 2008, he was appointed junior professor at RWTH and has been a professor of computer vision since 2011.

Tom Lüdde

Tom Lüdde has held appointments at the Hannover Medical School, the Lineberger Cancer Center in North Carolina, USA, the European Molecular Biology Laboratory, and the University of Cologne. In 2007 he took on a position at Uniklinik RWTH Aachen; since 2014 he has been professor of gastroenterology, hepatology and hepatobiliary oncology at RWTH Aachen University.

Source: Press and Communications