PhD Student with focus on computer vision algorithms using neural networks in an ambient assisted living context.

Master Thesis about optimization of convolutional neural networks for semantic segmentation in an automotive context.

Implementation of algorithms for encoding and transmitting high-quality videos for 360° Video for VR. As well as the implementation of adaptive http streaming methods on mobile devices.

Development and programming Front- and Backends using AngularJS and NodeJS.

Designing, developing and programming websites, mobile applications and databases according to customers requirements and first-level support.

Planning, developing and programming websites, mobile applications and databases, customer discussions and first-level support.

Administration of Windows Servers, developing Web- and Windows applications, firstlevel support for students and employees.

My dissertation addresses privacy concerns in computer vision by utilizing synthetic data to reduce reliance on real-world data for image processing. By employing computer-generated simulations, the work enhances deep learning models, particularly for object detection, and introduces domain adaptation methods to bridge the gap between synthetic and real data. Applications include Ambient Assisted Living, with systems for human pose estimation and activity recognition, all designed to preserve privacy and improve real-time performance without compromising data security.

Dissertation Topic: Improving Deep Learning-based Object Detection Algorithms for Omnidirectional Images by Simulated Data.

Master in International Media and Computing with focus on computer vision algorithms.

Thesis Topic: Examination of various methods for optimization and compression of neural networks (grade 1.3).

Bachelor in International Media and Computing with focus on computer vision algorithms.

Thesis Topic: Development of a system for Wifi-based control of a DSLR camera (grade 1.7)