I am interested in unsupervised deep learning learning, semi-supervised learning in domains with little labeled data and the cross-section between machine learning and computational neuroscience.
In my current work at the Institute for Image Processing and Computer Vision at RWTH Aachen University, I investigate deep learning algorithms for transfer learning and dense annotation of histopathological images.
As part of my Master’s program in Neuroengineering at the Technical University of Munich, I am currently on a research visit at the University of Kent, investigating deep learning algorithms for processing and analysis of EEG and other neurorecording data.
MSc in Neuroengineering
Technical University of Munich (2016 - present)
BSc in Electrical Engineering, Information Technology and Computer Engineering
RWTH Aachen University (2013 - 2016)
School of Computing, University of Kent since 03/2016
I am currently on a research visit in the labs of Caroline Li and Prof. Yi-Ke Guo and work on unsupervised learning methods for analysis of time-series data such as EEG.Implementation of our approaches is realized in TensorFlow and TensorLayer.
Institute of Imaging and Computer Vision, Aachen since 05/2016
Within the ILUMINATE project, I am working on deep learning algorithms for semi-supervised dense classification of histopathological images used in cancer research. Apart from deployment of networks in our software system, I worked on a novel approaches to apply deep learning in contexts with little available labeled training data. Used software packages are mainly Theano and TensorFlow.
RWTH Aachen University 09/2014 - 06/2015
Winter Term 2014: Mathematical Methods in Electrical Engineering, Prof. Merhof, Institute of Imaging and Computer Vision, Aachen, Summer Term 2015: Fundamentals of Electrical Engineering II, Prof. DeDoncker, ISEA, Aachen
Development of a software system for automated calibration of 3D camera systems as a preparation for sensor fusion algorithms, using C++, the Point Cloud Library and ROS.
TUfast e. V. Driverless Racing Team 2016 - present
At TUfast, we are developing an autonomous version of a Formula Student Racecar to participate in the Formula Student Driverless competition in Hockenheim. I work in the Sensors and Perception group on deep learning approaches for processing of sensor inputs.
Formula Student Team RWTH Aachen e. V. 2014 - 2016
I worked on the hardware and software design of data acquisition devices and the battery management system in the Formula Student racecars eace04 and eace05.
IT4Kids, Enactus Aachen e. V. since 2013
To provide children in primary school with courses in computer science, I founded IT4Kids in 2013 and build up the student initiative that is still active in Aachen as of now. With our classes, we have reached hundreds of pupils. The project was awarded the 3rd place at the Enactus National Competition 2015 and a winning project in the Google Impact Challenge (awarded 10.000 €). We also started the development of a flexible programming environment for pupils, combining advantages of Scratch and Python.
Development of a fully autonomous racecar for the FSG Driverless competition in Hockenheim.
M.Sc. Neuroengineering Student Blog with latest information about our study program and events.
ILUMINATE develops a novel platform for integrated analysis of in-vivo models for preclinical evaluation of new compounds in oncology, including innovative therapeutic approaches in oncoimmunology.