Centre for Advanced Analytics and Predictive Sciences
Data is a crucial raw material for present and future societies. Their inventive and intelligent modeling and analysis is a key to guiding future action. The Centre for Advanced Analytics and Predictive Sciences (CAAPS) therefore unites the data collecting and data processing foci of the University of Augsburg in a multidisciplinary center with the goal of enabling progress and innovation in method development - experimental and theoretical - and in actual applications.
The first Symposium of the Centre for Advanced Analytics and Predictive Sciences (CAAPS) takes place on October 19th, 2022 and begins at 4:30 pm. More information can be found here: Flyer_1Symposium_CAAPS .
The CAAPS Networking Days for PostDocs of all CAAPS disciplines take place on November 21-23th at Wissenschaftszentrum Schloss Reisensburg.
Recent developments in medical, computer-aided diagnostics and therapy, the production of high-tech materials and substances or the application of artificial intelligence, for example, show how closely data acquisition and data processing interact in current research issues.
Such developments require a research and development infrastructure consisting of a complex technological process chain and theoretical mathematical and computer science methods for processing extensive sensor information and data sets. This is not the only reason for the need for multidisciplinary cooperation between data collection and processing centers. Rather, it offers great innovation potential in economically and socially relevant research fields.
Die Universität Augsburg gründet im Dezember 2020 das Centre for Advanced Analytics and Predictive Sciences (CAAPS). Das CAAPS vereint (Mess-)Daten erhebende und Daten verarbeitende Schwerpunkte der Universität Augsburg in einem multidisziplinären Zentrum. Das Zentrum erhält große Unterstützung durch die bayerischen Förderprogramme HTA, HTA+ sowie den Innovationsfond.
In addition to the interaction of methodological approaches in the experimental field and the various data processing approaches in the theoretical field, the focus is on applications in quantum science, materials science, production science and medicine. At the same time, the development of the research area of life sciences is realized at the University of Augsburg.
High-resolution data acquisition and adapted data processing for the identification of relevant quantities are among the most important technologies to enable knowledge gain and innovation. In this context, the basic methodological orientation of the center makes it possible to address a wide range of questions.
At the CAAPS, modern computer-aided methods of image processing, data analysis and numerical simulation are made available to clinical medicine with the aim of improving the understanding of individual disease mechanisms and developments, diagnostics in the field of imaging and endoscopic procedures, the individual planning of complex therapeutic procedures and the prediction of therapeutic success.
Quantitative Life Science
Quantitative studies in life sciences are essential and a rapidly developing international research field. Here, fundamental physics and chemistry are combined with biology to address fundamental biological, biochemical, and biophysical questions. In order to understand active living matter across scales from DNA to the whole living being, it is necessary to develop innovative experimental measurement methods, mathematical prediction models and computer simulations.
The implementation of future technologies requires new engineered materials and adapted development strategies, while taking sustainability and resource conservation into account. The close interaction of computer-aided collection, monitoring, processing and interpretation of process and material data makes it possible to understand and control mechanisms of action. Both the production process and the use of materials as well as the desired component properties can thus be optimized while taking resource conservation and sustainability into account.
Quantum mechanical effects offer the possibility for novel data generation and processing. The laws of quantum mechanics allow, for example, high-precision measurements in quantum sensing or the use of quantum algorithms, quantum simulations and quantum computers in information processing. A better understanding for the use of quantum effects in practical applications requires accurate physical modeling in addition to experiments. Basic research on quantum matter and nanostructures enables to control quantum states, which are applied in a wide range of quantum technologies.
Integration into teaching
The handling of large amounts of data ("Big Data") and data science in general have gained immense importance in the past decade. This area stands between the classic disciplines of computer science and mathematics with applications in almost all fields of science. To ensure a sound education, the interdisciplinary interaction of these disciplines in teaching is imperative. Due to the importance of data science, the CAAPS will significantly and attractively expand the range of study programs at the University of Augsburg with joint courses in Data Science and Mathematics and Computer Science offered by the Faculty of Applied Computer Science and the Institute of Mathematics.
In addition, the master's degree program in Materials Science and Engineering (MSE) at the Institutes of Physics and Materials Resource Management will be expanded to include the promising pillars of Functional Materials and Structural Materials, with a focus on Digital Materials and Sustainability. This results in the creation of a materials science degree program with a clear profile in the topics of Digital Materials and Sustainability in English. Moreover, the recent topic of the application of AI-methods will especially be important in the recently restructured international degree program FAME (now FAME-AIS for „Functional Advanced Materials and Engineering – Artificial Intelligence and Sustainability).
The physics and computer science degree programs continue to gain in attractiveness due to new faculty appointments in the field of quantum sciences and quantum algorithms.
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