M.Sc. Kenny Schlegel
Research Interests
I am currently a Ph.D. student at the Chair of Automation Technology. My research interests are in the field of mobile robotics, especially visual perception and image processing. I have experience with classical image processing and self-learning algorithms, such as artificial neural networks. Furthermore, I work in the field of high-dimensional computing (see the links below for more information) and autonomous robot navigation (shopping assistance robots).
Further information:
Bibliometric Sources:
Events
09/2022 - Participation in the second Inria-DFKI European Summer School on AI at Saarbrücken, Germany
I was pleased to have participated in the second Inria-DFKI European Summer School on AI at Saarbrücken. On Track A (Trusted AI), we learned a lot about topics like explainable AI, machine learning in cyper-physical systems, compressive learning, etc. The five-day school was composed of talks, courses, and poster sessions.
07/2022 - Participation in the first Summer School on Neurosymbolic Programming at Caltech, Pasadena, USA
I was excited to be one of the 100 international students who attended the first Summer School on Neurosymbolic Programming at the California Institute of Technology. The three-day school included talks, tutorials, and a poster session around the topic of combining neural networks with symbolic program synthesis.
07/2022 - Visit of the Redwood Center for theoretical Neuroscience, Berkeley, USA
I had the pleasure of visiting the Redwood Center for theoretical Neuroscience in Berkeley to meet researchers from the field of HDC/VSA and give a Redwood seminar on "Exploring Vector Symbolic Architectures in Computer Vision and Signal Processing". Many thanks to my host Denis Kleyko (Research Institutes of Sweden)! The talk can be found here.
Tutorials
An Introduction to Vector Symbolic Architectures and Hyperdimensional Computing, ECAI 2020
We held a tutorial (tutorial website) on high dimensional computing at the 2020 European Conference on Artificial Intelligence (ECAI). We gave an introduction to properties of the high dimensional space, Vector Symbolic Architectures (VSAs), high-dimensional encoding of real world data, and applications. More information about the topic can be found in the following articles:
High dimensional computing - the upside of the curse of dimensionality, KI 2019
We held a tutorial (tutorial website) on high dimensional computing at the 2019 German conference on artificial intelligence (KI) in Kassel, Germany. We gave an introduction to properties of the high dimensional space, Vector Symbolic Architectures (VSAs), high-dimensional encoding of real world data, and applications. More information about the topic can be found in the following articles:
