Maximilian Wittig has been a research assistant at the Chair of Business Informatics IV at the University of Regensburg since 2020. During his studies he worked already as a student assistant at the same chair.
In his current position at the university, in addition to overseeing theses, P-seminars and theoretical seminars, he is also teaching algorithms, data structures, (object-oriented) programming and the security of mobile systems.
In research he focuses on pattern recognition and Machine Learning to protect personal data. In addition, he deals with questions relating to ensuring anonymity in location-based services and compliance with data protection aspects in distributed systems.
Chair of Business Informatics IV
Chair of IT Security Management or rather Chair of Business Informatics IV
Basics of programming (Object-oriented programming, Algorithms, data structures and programming), IT security (IT security 2, Security of mobile systems)
Our events do not relate to AI, but our seminar topics in the field of research do, e.g. Natural Language Understanding for a chat bot component on a platform for security incidents or the detection of tracker-loaded websites through machine learning processes and their evaluation.
Appropriate prior knowledge is taught in other courses, such as Big Data Analytics, Customer Relationship Management or in Data Analytics – Methods and Programming. Students must acquire in-depth knowledge themselves in the seminars via textbooks, specialist books or software documentation.
Depending on the type of seminar (theoretical or practical) theoretical or application-related basics about ML, such as pattern recognition through supervised learning and common software libraries.
Machine learning processes are mainly used in our seminars as a tool to efficiently process a problem because human intelligence is not sufficient. At the same time, it is a group of topics in which most students are very interested. They can benefit from the skills learned here in their later professional life.
The automatic detection of trackers in relation to advertising on the Internet with the help of supervised learning algorithms both on the application layer and on lower network layers.
In my studies of Business Informatics I attended the courses on Machine Learning and all statistics lectures. Then I wrote my seminar papers and master’s thesis on the subject of Machine Learning.
Question 10: Do you personally find it easy or difficult to deal with topics that are related to AI?
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The often surprisingly good results that an AI achieves when dealing with a task, e.g. the creation of music and the following comparison between the results of humans and machines.
No, currently there is no special collaboration that would be related to AI.
Ideally, there would be a separate course of study on the subject of AI and Machine Learning at the UR, such as Data Science.
As a chair with a main focus on IT security, we are currently not involved in any project related to “Knowledge creates² Data”. However, we are often looking for AI experts for internal projects, which we are partly search at the UR.
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Mr. Wittig, thank you very much for taking the time to answer these questions. We wish you a nice day!
Mr. Wittig, thank you very much for taking the time to answer these questions. We wish you a nice day!