Alexander Kinast studied Software Engineering at the University of Applied Sciences in Hagenberg in Upper Austria. During his studies, he worked part-time for around 2.5 years at the RISC Software GmbH as .Net software developer in the field of simulation and optimization. In September 2019 he joined the Data Science research network as PhD student, specializing in industry 4.0. He is interested in topics in the field of software development, metaheuristics, logistics and numerous subtopics of industry 4.0.
Dissertation
Combining metaheuristics and process mining to improve manufacturing processes
Industry and logistics currently experience a significant shift towards novel technologies such as different kinds of robots. The first goal of this dissertation is, that existing optimization algorithms are extended in a way, that they can handle these robots. This work's final aim is to combine metaheuristics and process mining algorithms. It is shown that a memetic algorithms performance can be boosted through a novel combination with a process mining algorithm.
What motivated you to pursue a PhD and how did you choose your field of research?
I worked on simulation and optimization during my bachelor and master thesis, and I found both areas interesting. The data science platform had an open job position for a PhD in the area of Industry 4.0. This position allowed me to combine both research areas and apply developed methods on modern problems.
To what extent was it beneficial for your research to be part of our research network Data Science?
Talking with other PhD students of the research platform has been beneficial for my work. Each person has an individual view on specific problems and since everybody cam from a different background, these could be helpful when thinking about solution methods for specific problems. During my whole study, all other members of the research platform have been supportive.
What was the most significant discovery of your research and how do you think it will impact your field and benefit our society?
That it can be beneficial to combine metaheuristics with process mining to solve complex problems in industry 4.0. Over the last centuries, metaheuristics have been combined with many different methods. However, it is necessary to think a bit out of the box, to combine them with new methods of other research areas.
What were the biggest challenges and how did you maintain your motivation and focus during your studies?
Having an interdisciplinary PhD position with two supervisors was challenging at some points. However, I think the biggest challenge was the combination of metaheuristics and process mining in a way, that it is beneficial for the base algorithm. Therefore, a large number of different runs had to be done on a supercomputer (VSC and HPC), which came with its own challenges. Since I could work with new technologies regularly and could focus my research on areas which I found interesting, it was not hard to stay focused and motivated.
What are your future career plans and how do you see your PhD degree influencing your professional trajectory?
Currently I work as Software Engineer in research and customer projects and teach at the university of vienna. Working on research projects would be hard without a PhD, as the PhD taught the skills needed for such projects. Teaching at the university is an interesting part of my work week, without my studies it would be hard to have the knowledge and confidence to teach there.
Please tell us why you stay affiliated to the research network.
I regularly visit my supervisor when I come to the university to teach. Additionally, Ill try to keep contact to my former colleagues.
