About Me
I am a post-doc researcher, originally from Germany but currently located in Tokyo, Japan. My biggest passion since my early youth is computer science. I was born 1990 in a super rural area in western Germany. While it was nice to grow up in a natural envirnment, I had a strong desire to break out of there and follow my dream of studying computer science. After I transferred from the Middle-School to the High-School (German: Gymnasium) and finished it, I moved to Bielefeld immediately to study Cognitive Informatics. I can definitely confirm, that this city exists, but most people from abroad probably wouldn’t know it. However, it is a great place to live and also a great place for studying computer science since there is a cluster of excellence (CITEC), which means great research conditions and a variety of possibilities for students. Also, people don’t study only computer science there, but computer science with a certain minor. I was studying Cognitive Informatics, which had computer science as major topic but with many links to a variety of cognitive sciences. Informatics alone might be a bit tasteless, but for me the combination with cognitive sciences makes it very interesting - especially for robotics where many cognitive models can be applied to. Also, what would be a better embodyment for state-of-the-art Machine Learning approaches than a robot? - Yes, there is none!
In my studies I focussed mainly on machine learning, computer vision and robotics. Regarding the latter, I e.g. competed with the Team of Bielefeld (ToBI) in the robocup@home German open competition and world championship in Hefei, China where in both competitions we won the 3. place. I liked especially to work very hard in a team of passionate people and to hack day and night to get the tasks done at the competition. I also attend smaller hackathons from time to time.
As a master’s project, together with a colleague I implemented an application with the Nao robot from Aldebaran, which we also evaluated within a user study. The application was a cooperative human-robot ball maze where the robot could also give suggestions where the human should navigate next. The cooperative human-robot topic I deepened afterwards in my PhD but more on this later.
Also, I was tutor during a major part of my studies, an activity that I found very pleasing (well, most of the time haha).
Cooperative ballmaze game with Nao robot.
In-field debugging at robocup@home competition.
For my Master Thesis I worked half a year at the company CLAAS KGaA mbH, the europen market leader in combined and forage harvesters. I developed a vision system for recognizing anomalies in front of the harvester. I greatly enjoyed working at this company building that big vehicles for nourish the world.
After finishing my Master Intelligent Systems, I decided to do a PhD on the topic of cooperative robotics. My PhD-position was within a cooperation with CITEC and the Honda Research Institute EU near Frankfurt, where I worked for over 3 years. In my studies I applied Active Learning in an Human-Robot-Interaction scenario which involved learning environments with a robot and the human in-the-loop. I found that it is crucial for an effective collaboration, that the robot has a competency model for both human and the robot itself. I introduced extensions for active learning models to achieving this conceiceness of the own and partners capabilities. Also, I introduced e.g. an interactive labeling interface, enable both diverse partners to work together effectively.
Service robot scanning lab environment for objects of interest.
I decided to continue my studies in a post-doc abroad. After a frustrating and challenging time of writing my thesis and the pandemic, I wanted to go to a country that is very different from my homecountry Germany to get some different input. As I found out about the post-doc scholarship of DAAD, I decided to apply for it at National Institute of Informatics (NII) in Tokyo, where I also was accepted. Tokyo is an awesome place to live and I growed alot in a personal and also in a professional way. In my post-doc I focused more on Neural Networks and Explainable Object Detection (Approach 1 and Extension) and also broaden my expertiese to Generative Models for e.g. Audio Sample Generation and Large Multimodel Models (LMMs). I think Transformer-based architectures and Large Language Models offer great possibilities for applications that wheren’t feasible in the past.
Deep Detection Dream - Image Reconstruction from YOLO BoundingBox Output.
Thinking back to my previous research, most revarding to myself is the combination of research and the practical implementation of an approach e.g. within a tech-demo application. I would say that my skill-set is versatile and allows me to do that.
If you want to learn more about me, take a look at my CV to get the most important facts in a compressed form. To read more about my interest, that haven’t directly to do with my profession, take a look at the Interests page. Also, I published some of my projects here.