Machine Learning and Artificial Intelligence at RUB
The ever growing machine learning and artificial intelligence research done at the Ruhr-University Bochum provides excellent opportunities for interested academics and industry partners alike. Since RUB researchers from a broad range of disciplines contribute to both fields, ml-ai.rub.de serves as an up-to-date register for core groups, study programs and projects.
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ProDi strenghtens the research network Protein Research Unit Ruhr within Europe – PURE. The PURE consortium develops innovative methods for the early diagnosis of cancer and neurodegenerative deseases such as Alzheimer’s. The total costs of the construction and the basic equipment totalling 48 million euros are borne by the federal government and the state of NRW. The construction phase began in November 2016. ProDi has opened June 3, 2019. |
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The new center will explore the interdisciplinary neuronal mechanisms of cognition, develop artificial and hybrid cognitive systems, and investigate the interaction between humans and technical systems in the working world of the future and in neurorehabilitation. The new research building will cover an area of almost 4,000 square metres. |
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The DFG-funded research unit FOR 2812 "Constructing scenarios of the past: A new framework in episodic memory" is made up of a group of 9 researchers. Seven from the Ruhr University Bochum and two from the University of Münster. We hail from 3 different fields:
Funding for this unit runs from 01.07.2019 - 30.06.2022. |
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In the research project "Kompetenzzentrum HUMAINE - Transfer-Hub der Metropole Ruhr für die humanzentrierte Arbeit mit KI (HUMAINE)", novel methods for the integration of artificial intelligence (AI) in exsisting, human-centered workflows are developed. The goal is a general improvement of work and everyday life quality. The project focus lies on innovative methods that specifically connect AI research to concrete application scenarios. Analysis and validation of the developed methods is done based on pilot projects in healthcare and industry. |
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The digital world has increasingly become a big part of our daily lives. Whether it's healthcare data, corporate disclosures, or state secrets: All this critical information is digitized today and has become accessible worldwide. Within the Cluster of Excellence CASA - Cyber Security in the Age of Large-Scale Adversaries at Ruhr-Universität Bochum, we are pursuing the goal of making the digital world a safer place. Our adversaries are powerful: The largest cyberattacks of our time often have well-organized, vast networks of cybercriminals or attackers with nation-state interests behind them. They have enormous financial resources and the technical expertise to cause long-term damage. Against these large-scale adversaries, today's security solutions are inadequate. This is why CASA brings together top-class scientists from various IT security disciplines to research sustainable countermeasures to create a more secure future for our digitized world. The strength of CASA lies in its unique holistic and interdisciplinary approach, which provides the basis for excellent research. That approach has enabled us to prevail over all our competitors and win a grant from the German Research Foundation (DFG) for the CASA Cluster of Excellence, which provides funding of 30 million euros over seven years. |
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SecHUMAN is an interdisciplinary research consortium that investigates the technichal and social challenges connected to IT security. Thereby, the focus lies on a holistic perspective that also includes political chances and risks resulting from developments in the field. The SecHUMAN consortium cooperates with partners from industry and politics to guide its research and is part of the Horst Görtz Institute at the Ruhr-University Bochum. |
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The objective of the project is to develop physical-based creep indicators based on composition, temperature and strain and to define them as parameters of a new property model for superalloys. Physical material parameters and mechanisms, such as gamma / gamma'-volume fractions, solid solution hardening and the kinetics of microstructure evolution, are individually evaluated with regard to their influence on the creep behaviour of the alloys. Methodically, a combination of regression analysis, data mining and machine learning methods is applied. |
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The iBain project aims to establish artificial material intelligence for optimising high-strength steels. Bainite, a specific steel structure, has outstanding mechanical properties due to its complex inner structure, which can be deliberately adjusted during production. This internal structure already places the highest demands on analysis and interpretation. Therefore, automatic pattern recognition and simulations are used to complement experimental findings. Statistical methods of experimental design (so-called "Design of Experiments") help to plan experiments and simulations, as well as to avoid redundancies. Finally, an automated control of the workflow and data flow is established. |
This website is intended to give an overview of the ever growing machine learning and artificial intelligence research done at the Ruhr-University Bochum (RUB). Since RUB researchers from a broad range of disciplines contribute to both fields, this website acts as an up-to-date register for interested researchers and students.
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