Dependence Modeling – PLUS

The team Dependence Modeling deals with random quantities and the multidimensional associations and dependencies that occur between these quantities; the range of applications is therefore extremely diverse.The group focuses on basic research concerning the evaluation, estimation, comparison and construction of such dependencies as well as its application to feature selection problems arising whenever multivariate data is available (finance, manufacturing industry, etc.).


Job advertisement: PhD position / 3 years

FWF-Project ReDim: Quantifying Dependence via Dimension Reduction, Project lead: Sebastian Fuchs


Postdoc-Position: Sebastian Fuchs

Bild S. Fuchs © Nils Eisfeld

Dr. Sebastian Fuchs is Senior Scientist at the Department of Artificial Intelligence & Human Interfaces at PLUS. He mainly works on topics in dependence modeling, quantitative risk management and nonparametric statistics with particular interest in financial and actuarial applications.

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Predoc-Position: Marco Tschimpke (ProSA)

M. TschimpkeMarco Tschimpke MSc completed his Bachelor’s and Master’s degree in mathematics at PLUS and focused on the field of probability theory and statistics. He is currently working on his PhD within a project with AMAG (ProSA project) and focuses on dependence modeling/detection and pattern recognition.

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Predoc-Position: Nicolas Dietrich

Bild N. DietrichNicolas Dietrich MSc schloss sowohl das Bachelor- als auch das Masterstudium in Mathematik an der PLUS ab. In seiner Masterarbeit beschäftigte er sich mit der Existenz von Lösungen für partielle Differentialgleichungen. Mittlerweile promoviert er im Bereich Abhängigkeitsmodellierung und Mustererkennung und befasst sich mit dem Konvergenzverhalten von Copulae.

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Student-Assistant: Anna-Lena Graf (FRIDA)

Bild AL GrafAnna-Lena Graf BSc completed her Bachelor’s degree in mathematics at the PLUS and is now pursuing her Master’s degrees in mathematics and data science. She is currently working on her master thesis within a project with Porsche (FRIDA project), focusing on pattern recognition and optimization.

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