Research

I am and have been involved in many research projects since my Bachelor's study. Although I love to work theoretical, many projects lead to practical applications or experiments and I am always eager to dive into a new topic of my field.

This page highlights some of the projects I worked on (together with unpublished work) while my publications can be found here.

 

 

 


 Learning Turtle Locomotion: By using Sparse Latent Space Policy Search locomotion for a paper robot was learned. Find more information about this research project on www.c-turtle.org.    Sparse Latent Space Policy Search: Another algorithm which combines dimensionality reduction & reinforcement learning. The algorithm makes use of inherent structures, like legs & arms, to find group specific manifolds and reduces the amount of required samples for learning.
 
   
 Nano- and Microrobotics: On my stay in Finland I worked on a small, unpublished, project in Quan Zhou's lab. We tried to move particles directed by Chladni patterns created by vibrating Piezo elements in combination of Machine Learning. I had also the chance to try out their micro-manipulator.    Latent Space Policy Search: The first algorithm I developed which combines dimensionality reduction & reinforcement learning into one framework. It is based on PPCA and Policy Search. We used it to let a NAO robot learn to lift its leg, both in simulation and applied on a real robot.
 
   
 BCI & Machine Learning: Also in Finland I worked with a colleague (in the picture) on applying Machine Learning methods on EEG data from the brain. The goal of this unpublished work was to predict if a person recognizes a person.