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On October 30, 2018, I gave my research talk Automating Scientific Research in Optimization at the chair for Artificial Intelligence and Software Technology (KIST) of Prof. Dr. Manfred Schmidt-Schauß at the Computer Science Institute, Computer Science and Mathematics Department of the Goethe University Frankfurt in Frankfurt am Main, Germany.

Prof. Schmidt-Schauß and his group are following several highly interesting strands of research centered around functional programming languages and program analysis. For instance, they work on the static analyses of programs and expressions, including termination analysis, demand analysis, and strictness analysis, which are important topics for compilers of (non-strict) functional programming languages. They work on understanding the observational semantics of functional programming languages with call-by-need evaluation in the contexts of studying extended lambda-calculi and concurrent computation. Another one of their research topics is understanding the side effects of input/output operations in lazy functional programming languages. They also conduct research on unification, i.e., solving equations in a logical form, encompassing unification in equational theories, sorted unification, combination of unification algorithms and unification in higher order logics. Finally, they work on knowledge representation, and investigate the properties of concept description languages and their reasoning behavior and complexity.

It was very nice to meet Prof. Schmidt-Schauß and his group. I am very thankful for their hospitality and for the nice discussion as well as the kind reception of my talk.

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On October 29, 2018, I gave my research talk Automating Scientific Research in Optimization at the Simulation and Modelling (SIM) group of Prof. Dr. Helena Szczerbicka at the Institut of Systems Engineering (ISE) of the Leibniz University Hannover in Hannover, Germany.

The SIM group conducts fundamental and applied research in the fields of modeling, simulation, and optimization. They are especially interested in the modeling of complex systems (such as technical processes) with discrete simulations, stochastic Petri nets, and multi-agent systems, the analysis of models, the simulation of algorithms in the domain of "search & rescue", bio-inspired algorithms for optimization of networks, anomaly detection, online simulations for control (e.g., in construction side vehicles and heat distribution networks, as well as algorithms and standards for co-simulation (e.g. ACOSAR). Prof. Szczerbicka furthermore is a highly respected member of the Society for Computer Simulation International, in which she had several leading positions for several years.

It was very nice to meet Prof. Szczerbicka and her group and my presentation was received well. I very much enjoyed the very interesting and inspiring discussion afterwards.

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On October 26, 2018, I gave my research talk Automating Scientific Research in Optimization at the junior professor chair for information systems and operations research of Prof. Dr. Lin Xie at the Institute of Information Systems (IIS) of the Leuphana University of Lüneburg, Germany.

Prof. Xie has contributed valuable research on applied optimization, covering topics such as automated warehousing fulfillment systems and crew rostering. She emphasizes on the importance of modelling for making complex decisions. Application areas with such scenarios are often logistics and transportation, such as public bus systems. Another application field processed by Prof. Xie and her group is the assessment and developments of algorithms for routing multiple robots through warehouses in order to transport items for storage. This work is actually quite related to our research direction on rigorous performance analysis of algorithms, but also features other important aspects. Her other areas of interest include operations research and data science.

Meeting Prof. Xie and her group was very nice and my talk was received with interest by a large audience. The positive feedback on the talk was very encouraging and the following discussion with Prof. Xie was very interesting – especially since our works on algorithm analysis are highly related.

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On October 25, 2018, I gave my research talk Automating Scientific Research in Optimization at the CSLog research group of Prof. Dr. Nicole Megow at the Fachbereich 3: Mathematik/Informatik, University of Bremen in Bremen, Germany.

The research of the CSLog group is centered on combinatorial optimization, often on the interface between logistics, mathematics, and computer science. They analyze the structure of discrete problems and design efficient algorithms with provable performance guarantees for solving them. Another strand of research is on solving combinatorial problems under incomplete information, as well as the development online, stochastic or robust algorithms. They contribute theoretic results and also apply them in complex real-world environments. The typical application areas are scheduling, production planning, logistics, network design, communication and routing in networks, and health care.

The application areas interesting for CSLog are very similar to those interesting to our team, which made the visit even more interesting for me. The audience of my talk was interested in the presented concepts and we had a nice discussion afterwards. I was very happy to meet Prof. Megow and her group and found the outstanding rigor and quality of their work very impressing. From our discussion, I could take home several new ideas, so the exchange the thoughts was definitely helpful for me. 

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On October 24, 2018, I gave my research talk Automating Scientific Research in Optimization at the Computational Intelligence research group of Prof. Dr. Oliver Kramer at the Department of Computing Science, School of Computing Science, Business Administration, Economics, and Law of the Carl von Ossietzky University of Oldenburg in Oldenburg, Germany.

The Computational Intelligence group contributes research on many topics centered around evolution strategies and deep learning. Prof. Kramer is particularly focused on recurrent, convolutional, as well as large-scale neural networks, often in relationship with optimization methods such as evolutionary algorithms or swarm intelligence approaches. Other fields the group works on are dynamic and multi-objective optimization, scheduling, and machine learning for optimization or marine time series.

After having worked with Prof. Kramer on two papers remotely, I was very excited and happy to finally meet him in person. It was also very nice to present our work, which uses machine learning to analyze optimization algorithm performance, in front of a group that, too, combines machine learning and optimization. My talk was well-received and led to very nice discussions afterwards. I also had the chance to attend two Master's thesis presentations, which were both very interesting. What impressed a lot was the high enthusiasm for their subject that all of the team members of Prof. Kramer showed – enthusiasm which leads to excellent results.

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