Short Bio

Dr. Mirko Kück is a strategic project leader for the development of data science and artificial intelligence solutions regarding supply chain management and vehicle commissioning at the organizational unit "Production & Supply Chain Management" of Mercedes-Benz in Bremen, Germany. He develops sustainable processes in order to optimize the key performance indicators of the global production network of the company. In addition, he is the product owner of a system of digital tools for management reporting and expert analysis. Furthermore, Dr. Kück leads publicly funded research projects, such as the cooperation project with the University of Bremen "AutoCBM - A meta-learning approach for automatic condition-based maintenance". Prior to this Dr. Kück was working as a project leader and data scientist in the strategic maintenance organization of Mercedes-Benz. In this role, he primarily led digitalization and Industry 4.0 projects to develop predictive maintenance applications, but he also conducted data science projects in other areas, such as quality control and production economics. In 2019 he was leading the project "Predictive rework" at Mercedes-Benz U.S. International in Alabama, USA.

Apart from his daily work, Dr. Kück is serving as a lecturer at Hochschule Bremen - City University of Applied Sciences. Currently, he is holding the lecture "Scientific Working", in which he teaches students the scientific research process regarding the central question: "How do novel Large Language Models affect business, industry and society?". Moreover, he is responsible to teach engineers, workers and managers in the areas of data science, business analytics and artificial intelligence, so that they gain the ability to utilize innovative analytics and data science tools in their daily work. Prior to that, Dr. Kück served as an invited lecturer at the Federal University of Santa Catarina (UFSC) at Florianopolis, Brazil to hold the lecture "Theory and Applications of Data Science and Artificial Intelligence in Operations Management", in which he followed the research-based learning approach, leading to three published articles by the students in international journals or conference proceedings.  From 2018-2019 Dr. Kück was a lecturer at the faculty of Production Engineering at the University of Bremen, holding the lecture "Modeling, Analysis and Control of Dynamics in Logistics". Furthermore, he has been supervising student projects as well as multiple Master and Bachelor theses as second supervisor.

Prior to that, Dr. Kück was a research scientist at the BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen. He studied Mathematics at the University of Bremen with a particular emphasis on Statistics and Business Economics as an additional subject. After graduating with the German diploma (Dipl.-Math., grade "very good") in 2010, he joined the BIBA as a research scientist and project manager. From 2016-2018 he was leading an international team of 20 members from research and industry working on different research projects in the areas of data-driven control of production and logistics systems, digital twins as well as data science for predictive maintenance. Moreover his Ph.D. (Dr.-Ing.) thesis was awarded with summa cum laude at the University of Bremen regarding the research topic "Selbination - A hybrid meta-learning approach for the automted selection and combination of suitable time series forecasting models for production planning" and he was awarded with the "Wissenschaftspreis Logistik" of the BVL - Bundesvereinigung Logistik.

Over the years, Dr. Kück successfully acquired several externally funded grants (DFG, DAAD, IIF, WFB, BAB) for original research projects as well as international research visits. From 2016-2018 he was a visiting researcher at the Department of Production and Systems Engineering of the Federal University of Santa Catarina (UFSC), Florianópolis, Brazil.

Among other topics, Dr. Kück is currently conducting research in the areas of smart production and logistics. In order to solve the complex and dynamic problems, he mainly applies methods from data science, machine learning, meta-learning, statistics, modeling and simulation, simulation-based optimization, time series forecasting, neural networks and artificial intelligence. Dr. Kück published 28 articles in international journals and conference proceedings and also served as a reviewer for many. He presented his work on several national and international research conferences as well as business and industry workshops. Besides, he also organized a research conference and industry meetings.