Prof. Dr. Alexander Schiendorfer

Possible applications of combinatorial optimization and machine learning in production & logistics, especially with the requirements of the automotive industry (assembly-intensive, variant-rich production, complex supply chains)

• Constraint programming, mathematical optimization (e.g. MiniZinc, Google OR-Tools, Gurobi, CPLEX)
• Machine learning (uncertainty-aware deep learning, reinforcement learning, graph neural networks)

Ongoing research projects:

• PALIM
• IKIGas
• PRepAIr
• NEwAIste
• FEDIMA

• Since March 2021 Research professor für AI-based Optimization in Automotive Production, Technische
                                Hochschule Ingolstadt
• 2018-2020           Senior researcher (untenured), Institut für Software & Systems Engineering,, University of
                                Augsburg
• 2013-2018            Research associate and doctorate in computer science, Institut für Software & Systems Engineering,, University of Augsburg
• 2011-2013            M.Sc. Software Engineering (University of Augsburg, TUM, LMU - Elite graduate program)
• 2011                      Research internship at Siemens Corporate Research (Princeton, USA)
• 2011                      B.Sc. Software Engineering (Hagenberg, Austria)

Full CV available upon request
( https://www.linkedin.com/in/alexander-schiendorfer/ or https://twitter.com/schienal ) 

see https://scholar.google.at/citations?hl=en&user=NDP4if4AAAAJ or https://opus4.kobv.de/opus4-haw/solrsearch/index/search/searchtype/authorsearch/author/Schiendorfer%2C+Alexander