Orell Trautmann

Research interest

My field of research is mainly related to the inspiring world of network theory. Currently, I am focusing on network-based methods for drug predictions. However since the techniques from network theory are so broadly applicable, I am also researching in network analysis outside of the biological context.

Furthermore, I am also interested in deep and machine learning models. My focus here lies on their intersection with networks or graphs, e.g. graph convolution neural networks or network embedding learning. I am especially interested in the construction of  good network representations for down stream tasks such as link prediction or node classification for general networks (Multiplex networks, Multilayer networks or hypergraphs).

Education and Work Experience

2023 – Today

Research and teaching assistant at the Department for Systems Biology and Bioinformatics
University of Rostock, Germany

2022 – 2023

Master 2 studies in Mathematics
Focus: stochastic calculus, Markov processes and machine learning
Sorbonne University Paris, France

2019 – 2022

M. Sc. Mathematics
Focus: partial differential equations and optimal control theory
Technical University Berlin, Germany

2018

Student Assistant
Fraunhofer IGP: Modelling with measurement data
Rostock, Germany

2014 – 2019

B. Sc. Mathematics
Focus: functional analysis, with a minor in theoretical physics
University of Rostock, Germany

2012 – 2014

International Baccalaureate (Bilingual Diploma English / German)
Higher Levels: Mathematics, Physics and Chemistry
International School of Berne, Switzerland