Simon Bremer

• Research of state-of-the-art recommender systems and evaluation metrics • Design of a hybrid framework to combine collaborative filtering and content-based methods • Custom, high performance implementation in Python/Pandas + Keras (Theano/GPU) • Performance evaluation with structured testing methods and multiple measurement metrics • Publishing and presenting the results at KTL workshop at the RecSys2017 conference Source: https://github.com/sbremer/hybrid_rs

• Design of a custom, multi-stage classification framework for visual object recognition • Implementation of the framework and multiple classifiers using Python (OpenCV/sk-learn) • Performance evaluation, deployment and live testing of the solution • Real time filtering of sensory data for event triggering • Giving Machine Learning workshops to employees • Assessing applicants during recruiting

Focus: • Distributed Systems • Machine Learning and Inference • Artificial Neural Networks

Thesis: A Framework for Training Hybrid Recommender Systems, Focus: • Machine Learning • Computer Vision • Advanced Programming • Neural Engineering • Computational Neuroscience

Thesis: Anomaly Detection with Event-Based Vision: Detection of Broken Cogwheels in a Running System, Focus: • Computational Intelligence • Speech- and Image-Processing • C/C++ • Human-Machine Communication