Robert Jackermeier is a research fellow at the Chair of Information Science at the University of Regensburg. Before taking up this position, he was a research assistant at the same chair and completed a Bachelor’s degree in Media Informatics & Information Science and a Master’s degree in Information Science.
His courses focus particularly on the topic of data analysis and visualization. For example, he is in charge of the course “Analyzing and Visualizing with Python” for students of the Digital Humanities Masters course.
In addition to his teaching, he is responsible for improving and developing the campus navigation URwalking .
Chair of Information Science
Question 1: Mr. Jackermeier, at which chair / institute at the University of Regensburg do you work?
At the Chair of Information Science
I have only recently started teaching, so the common thread in my courses has been data analysis and visualization.
In the course “Analyzing and Visualizing with Python”, the use in the area of machine learning is also addressed, but not dealt with in particular.
In this case, no previous knowledge is required, it is an introductory course.
Programming with Python has emerged as the de facto standard for using machine learning libraries and is almost indispensable if one wants to pursue a career in this field.
I always find it important to have a basic understanding of the technologies used in everyday life. In addition, knowledge in the field of AI/Machine Learning/data science will certainly be in greater demand on the job market in the future than it is today.
I am working on improving the positioning for our campus navigation URwalking, especially indoors where no GPS is available.
Not with AI in the strictest sense, but we have already successfully used ML methods to classify user activity based on motion sensor log data.
Above all, I have experience in the use of tools such as Keras and Tensorflow and the administration of the hardware and software used for them. I acquired most of this knowledge myself in the course of my doctoral studies; at the time of my Master’s degree, the topic of AI was not yet prominently represented in the curriculum.
Question 10: Do you personally find it easy or difficult to deal with topics that are related to AI?
Since I’ve always been interested in new technologies, it is rather easy for me. As long as you don’t want to understand the mathematical background in detail, there are surprisingly catchy concepts behind many AI methods.
In this context, I find the prospect that more and more work – and not just the apparently low-skilled – can be done by machines exciting. Of course, this raises social questions that will certainly be with us for the next few decades.
It would certainly be desirable when in all subjects that touch the topic basic AI skills would be taught. Not necessarily with a technical focus, but rather to get a basic feel for the current possibilities of AI.
I welcome the interdisciplinary collaboration and hope that it will result in many exciting projects. My contribution is currently limited to making sure that the website and our machine learning servers run smoothly.
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Mr. Jackermeier, thank you very much for taking the time to answer these questions. We wish you a nice day!
Mr. Jackermeier, thank you very much for taking the time to answer these questions. We wish you a nice day!