Teaching
For me, teaching is to not only deliver material or provide answers to my student audience, but rather to:
- provide fundamental knowledge in breadth and depth.
- provide skills to be able to discuss this knowledge critically and to implement it correctly and efficiently in engineering applications.
- pass on a piece of my enthusiasm for simulation and application of Scientific Machine Learning (SciML) in engineering in every teaching and mentoring situation.
In my lectures, I use interactive and project-based learning, hands-on working on projects and hearing from leading representatives out of academia but also industry.
The digital transformation of the ACEO community in the years ahead in my eyes requires to recover and pass on the spirit of master builders of the renaissance as especially the use of SciML requires cross-domain knowledge while civil engineering is inherently an applied science where real projects should be brought into the classroom.
I have teaching experience as lecturer at Technical University Munich, Bundeswehr University Munich, Technical University Darmstadt, and ETH Zurich.
Theory
Transmit fundamental knowledge in breadth and depth.
Application
Be able to discuss the knowledge critically and to implement it correctly and efficiently in engineering applications
Enthusiasm
Courses
Scientific Machine and Deep Learning for Design and Construction in Civil Engineering
In recent years, the Artificial Intelligence technology was introduced to the Architecture, Engineering and Construction (AEC) industry. Numerous application achievments have since been reached in this interdisciplinary field. However, yet today fundamental questions...
Frontiers in Machine Learning Applied to Civil, Env. And Geospatial Engineering
With the increasing amount of data collected in various domains, the importance of data science in many disciplines, such as infrastructure monitoring and management, transportation, spatial planning, structural and environmental engineering, has been increasing. The...
Artificial Intelligence for the Building Industry
Attempts to develop artificial intelligence have been underway for decades. As early as 1950, Alan Turing developed the famous Turing test and was the first serious proposal in the philosophy of artificial intelligence.For most of the time since then, machine learning...
Doctoral Seminar Data Science and Machine Learning in Environmental and Geospatial Engineering
Current research in machine learning and data science within the research fields of the department. The goal is to learn about current research projects at our department, to strengthen our expertise and collaboration with respect to data-driven models and methods, to...
Seminar “Probabilistic Machine Learning for Civil Engineers“
This one-day seminar was conducted at TU Darmstadt to provide an introduction to Artificial Intelligence, Machine and Deep Learning for a civil engineering audience from academia and industry.
Actions, structural reliability, artificial intelligence and Machine learning
I delivered two lectures and two exercises on reliability in civil engineering, uncertainty quantification as well as background and application of Artificial Intelligence for master students of Civil Engineering.