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Graphs in Artificial Intelligence
and
Neural Networks

GAIN Group Members

Currently, the GAIN-group consists of group leader, Ph.D. studentsandas well as student assistants,,and.

In addition,Prof. Dr. Bernhard Sick, head of the Intelligent Embedded Systems department of the University of Kassel, is our mentor. And, senior scientist in Machine Learning and group leader at Fraunhofer IEE, is project leader at our project partner Fraunhofer IEE.


If you are interested in joining us, feel free tocontactus. We have one more Ph.D. student position coming up at the Fraunhofer IEE in the second half of the year 2021 and might need an additional student assistant.

Dr. rer. nat. Josephine Thomas

Josephine is the leader of the junior research group GAIN.

She is a trained physicist and gained her doctorate with a thesis on non-linear dimension reduction applied to a topic of complex network theory.

She choose to work on Machine Learning and specifically on GNNs because she likes to do basic reseach but also see it go to a useful application quickly and because graphs are just cool: they can describe the formation of the universe as well as the internet, what more can a scientist want?

Her focus in GAIN next to supervising PhD students is the explainability of the dynamic algorithms.



Areas of Interest:

Graphs, deep learning, network geometry, quantum physics, renewable energies.



E-mail:

Phone: +49 561 804 6061

PGP-key: Download here

M.Sc. Silvia Beddar-Wiesing

Silvia is working towards her Ph.D. in the GAIN group with Dr. Josephine Thomas and Prof. Dr. Bernhard Sick as her supervisors.

Silvia graduated with a B.Sc. in mathematics and a M.Sc. in computer science with a specialization in Computational Intelligence and Data Analytics at the university of Kassel.

Her research topic addresses the analysis of dynamic heterogeneous graphs using Neural Networks. The focus is on Machine Learning tasks for structure-changing graphs, such as temporal Graph Generation, Graph Embedding Learning, Predictions and Novelty Detection.



Areas of Interest:

Pattern Recognition, Machine Learning, Combinatorial Optimization, Time Series Analysis.



E-mail:

Phone: +49 561 804 6454

PGP-key: Download here

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M.Sc. Alice Moallemy-Oureh

Alice graduated with a M.Sc. in Mathematics and its applications to Computer Science, from the university of Kassel. Her specialisation in Mathematics lies in Algorithmic Commutative Computeralgebra and Geometry. In Computer Science, she focused in Logic and Data Analytics.

Currently, Alice is a Ph.D. candidate in the GAIN Group. Her research is in the direction of the analysis and development of various Neural Networks on graphs that are affected to a wide range of dynamics.



Areas of Interest:

Geometric Deep Learning, Machine Learning, Pattern Recognition, Commutative Computeralgebra, Geometry, IT-security.



E-mail:

Phone: +49 561 804 6363

PGP-key: Download here

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Eric Alsmann



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Björn Schröder



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Marie Kempkes



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Rüdiger Nather



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Cooperations

We are funded by the Federal Ministry of Education and Research Germany (BMBF), under the funding code 01IS20047A, according to the 'Policy for the funding of female junior researchers in Artificial Intelligence'.

The responsibility for the content of this website or of any publication lies with the author.