High attendance of the VGU at the RUB


On Friday, May 10, 2019, the Faculty received an important visit from Dr. Hà Thúc Viên (Vice President for Academic and Student Affairs) of the Vietnamese-German University (VGU).

Participants of the meeting with Dr. Hà Thúc Viên from Vietnam on the part of the RUB were Prof. Dr. rer. nat. Klaus Hackl and Dipl.-Ing. Jörg Sahlmen. The event was accompanied by Dr. iur. Dietmar Ertmann, Chancellor of the University of Karlsruhe a.D. and board member of the Consortium Association VGU e.V., responsible for finances. Together they discussed the introduction of a double-degree agreement between the RUB and the VGU for the international master course Computational Engineering. The English-language Master's course has been established at the Faculty of Civil and Environmental Engineering for 20 years. In Vietnam, the sister course of the same name was introduced at the VGU in 2009, where the RUB had been leading the course for eight years and also awarded the Ruhr-University Master's degree for nine years. This year, coordination was handed over to VGU, which now operates Computational Engineering as the first course of study at VGU under its own direction with its own degree.

The Consortium Association VGU e.V., which was founded in 2009 in the DAAD Bonn, and its member universities form the academic basis of the VGU. Its members currently include 35 universities and university institutions (including the RUB - TU Berlin, TU Braunschweig, TU Darmstadt, Goethe University Frankfurt, University of Marburg and others). The Consortium Association VGU e.V. supports and coordinates the activities of the German partner universities of the VGU and at the same time supports the transition to independence. The Consortium Association VGU e.V. is supported by the Federal Ministry of Education and Research (BMBF) and the Hessian Ministry of Science and Art.

VGU meets RUB

Prof. Dr. rer. nat. Klaus Hackl, Dipl.-Ing. Jörg Sahlmen, Dr. Hà Thúc Viên and Dr. iur. Dietmar Ertmann (from left to right)


On the 7th of May, 2019, the Center for Higher Education (CHE) published the new CHE University Ranking 2019/2020. Nine out of the seventeen evaluated Departments are offered at RUB: English Studies, Civil Engineering, Electrical Engineering and Information Technology, German Studies, Mechanical Engineering, Psychology, Environmental Engineering and Materials Engineering. Within the framework of the CHE University Ranking, students are asked about the study conditions at their university. In total, the CHE Ranking includes more than 150,000 surveyed students and more than 300 universities and universities of applied sciences. This makes the CHE Ranking one of the most comprehensive and detailed university comparisons in German-speaking countries.

The Faculty of Civil and Environmental Engineering and its range of courses were convincing in the areas of 'Support at the beginning of the study', 'Contact to professional practice in the Master's programme', 'International orientation in the Master's programme' and 'Doctorates per professor'. We are very proud to be part of this faculty.

Excerpts of the CHE Ranking were published in the German magazine "ZEIT Studienführer", which supports prospective students in their choice of study as well as in the WAZ (largest regional newspaper in Germany).

The complete evaluation of the RUB study programmes in the context of the CHE University Ranking can be found on the website of ZEIT CAMPUS ONLINE.



Christina Rauch, Student Assistant



Jun.-Prof. Dr. Andreas Vogel and B. Sc. Jose Pinzon Escobar, members of the working group High Performance Computing in the Engineering Sciences, are delighted to win a prize of 5,000 euros for their eLearning concept "CodeRunner for student software development for high-performance computers". The RUB's eLearning team honored innovative eLearning solutions in the 23rd round of the competition according to the motto "Hitting the Bull's eye with eLearning".

In order to reliably answer engineering and physical questions, massive computing power is required in some cases, so that appropriate simulations and evaluations can be carried out. In his courses, Jun.-Prof. Dr. Andreas Vogel provides students with the necessary overall understanding for the use of high-performance computers (computer clusters), the properties of suitable mathematical solution algorithms and the implementation of programming techniques. Along with B.Sc. Jose Pinzon Escobar, the question "How can we learn programming techniques even better?" arose in January 2019, which led to participation in the competition.

The presence exercises of Jun.-Prof. Dr. Andreas Vogel are aimed particularly at students of the international Master's program "Computational Engineering". The programming knowledge of the students varies, which is caused by the different backgrounds of their bachelor studies. In most cases, however, the necessary time is lacking to deal in detail with the programming difficulties of individual students. So far, the solutions have been presented by the lecturer and made available to the students in order to continuing to work on this level of knowledge. Jun.-Prof. Dr. Andreas Vogel wants to improve the learning processes immediately, because he is sure that: "You have to practice programming practically in order to achieve a better learning effect". Together with the students and Jose Pinzon Escobar, he therefore initiated an open discussion round in January. During the search for solutions, the project idea for eLearning methods finally emerged.

Jun.-Prof. Dr. Andreas Vogel and Jose Pinzon Escobar subsequently developed the award-winning eLearning concept, which enables students to learn at their own learning pace. The implementation takes place in the form of weekly programming exercises that build on each other and deepen the learning process. Small code snippets are gradually programmed in question-answer mode. At the same time, their correctness is tested automatically. After checking the partial step, only the next partial task can be solved and the correctness of the implementation can be tested. Accompanying comprehension questions (multiple choice, answer input) support the students to understand the characteristics and essential aspects of the tasks better. By achieving the learning goal in various levels, Jun.-Prof. Dr. Andreas Vogel and Jose Pinzon Escobar create both a sense of achievement and a high motivation to independently solve programming tasks (gamification). Thus, students develop a fully functioning software program at the end of the course, which can be run on the largest parallel computers. While searching for supporters, Jun.-Prof. Dr. Andreas Vogel and Jose Pinzon Escobar came across the 5x5000 eLearning competition and were able to convince the student jury of their idea. For the introduction of the new eLearning methods, the use of a plug-in for Moodle is already planned in cooperation with RUB IT.SERVICES. After a test phase, further development will take place during the semester.

In the course of the RUBeL competition, the eLearning team supports innovative eLearning projects at the RUB. The planning and implementation is in the hands of students. Further information on the competition can be found here.

We congratulate the award winners and wish them continued success in implementing the project!


Lina Böhme, PR Department



On Friday, the 5th of April 2019, CompEng set out for the annual “Hannover-Messe”, the world’s leading industrial fair. At 7 in the morning we started our journey to the exhibition site in Hannover which consists of 26 fair halls on a 496,000 m² area. Therefore, it is the largest exhibition site in the world.

After our arrival we had the whole day to experience and discover the different facilities and offers as well as to talk to companies about graduate jobs, external master’s theses or internships.

“Integrated Industry – Connect & Collaborate” – that was the lead topic of this year’s Hannover fair, underlining the growing importance of artificial intelligence and machine learning in the production and energy industries. Technologies for the factories and energy systems of the future, more than 500 use cases for Industrie 4.0 as well as Machine Learning, 6,500 exhibitors from 75 countries and much more awaited us - time was short to experience all that the fair had to offer.

The nice weather and good mood made for a successful trip. After a day full of new impressions, we were ready for a nap on the way back on the bus.

Thanks for everyone who participated. We really enjoyed the trip!



Christina Rauch, Student Assistant

New member for the CompEng Lecturer Team: Interview with Prof. Dr. Tobias Glasmachers

We are happy to announce that from the summer semester 2019 Prof. Dr. Tobias Glasmachers will be joining the CompEng lecturer team. The lecture “Machine Learning: Supervised Methods” will be part of the CompEng curriculum.

He received his PhD from the Faculty of Mathematics at the Ruhr-University Bochum while working in Christian Igel's group at the Institute for Neural Computation at the RUB. In 2009 Prof. Dr. Glasmachers left Bochum and took a position as a post doc in Jürgen Schmidhuber's group at IDSIA, Lugano, Switzerland. After 3 years, his way led him back to the Ruhr-University. First as Junior professor for theory of machine learning at the Neural Computation, followed by the promotion to a full professor in 2018 at the same institute. In the following interview Prof. Dr. Glasmachers gives a short inside into his research field and why machine learning is becoming an important field in engineering.


Since 2018 you have been holding a full professorship at the Institute for Neural Computation at the Ruhr-University Bochum. At first glance, this has less to do with engineering science, especially with Computational Engineering. What is your research profile?

My research interests are machine learning and optimization. These two areas are intimately connected: optimization algorithms are the very basis of nearly all training procedures. From a methods perspective, machine learning is indeed rather different from engineering, however, the problems tackled are often very similar.


What does Machine Learning mean?

Machine learning is all about training predictive models from data. These can be full-blown process models, but often they are reduced to simpler tasks like classification. The data-driven approach, in a sense, contrats engineering. Instead of using expert knowledge and human problem understanding, the training algorithm figures out by itself how to build the model, relying only on the training data. Hence, models are built in an automated way, and they automatically improve as more data becomes available. However, in practice this does not mean that the human expert is completely outside the loop. Data scientists select and validate suitable model types and tune their parameters to the task at hand. More often than not, engineering expertise is key to success, as it guides the important process of data cleaning and preparation.


What future prospects does Machine Learning offer in the field of engineering?

Machine learning is becoming increasingly important in engineering, and there is a strong demand from industry for engineers with this competency. It is of particular interest in domains where exact modelling is infeasible, either due to limited knowledge, or due to overwhelming complexity, and where data is available or easy to obtain. Autonomous driving is an excellent example of such a problem domain. Machine learning is a very general tool, and as such it finds applications in nearly all sub-fields of engineering.


What possibilities do students have to further explore the field of machine learning?

The Institute for Neural Computation ( offers a whole series of courses on the topic, for example unsupervised learning and a specialized course on deep learning for computer vision. Nowadays there are also plenty of online courses available. There is excellent and easy-to-use open source machine learning software available for everyone, so getting your hands dirty is easier than ever.