Michael Schelling completed his masters degree in mathematics in 2015. Following this, he worked at the institute of communications engineering before joining the research group Visual Computing in November 2018.
Research interests
Neural Networks in general
- on 3D point clouds
- on 2.5D data
- for depth correction
- equivariance
Lectures, Projects and Seminars
Past semester as scientific assistant:
- Seminar: Research Trends in Visual Computing (recurring)
- Deep Learning for Graphics and Visualization (WT19/20)
- Workshop: Deep Learning for Graphics and Visualization (ST19)
- Channel Coding (WT17/18)
- Communications Engineering Seminar: Wireless Communications (WT17/18)
- Applied Information Theory (ST17)
- Communications Engineering Seminar: Cryptography: Algorithms, Applications and Standards (ST17)
- Introduction to Communications Engineering (WT16/17)
- Theory of Digital Networks (ST16)
Past semesters as student assistant:
- Functional Analysis (WT14/15)
- Elements of Differential Equations (ST14, ST13)
- Ulm University Trainingscamp (ST14, ST13)
- Analysis 3 (WT13/14
- Elements of Complex Analysis (ST13)
- Analysis 2 for Computer Scientists and Engineers (WT12/13)
- Analysis 1 for Computer Scientists and Engineers (ST12)
- Linear Algebra for Computer Scientists and Engineers (WT11/12)
Theses
I am happy to supervise theses in the field of neural networks, feel free to drop by at my office.
