My experiences so far stem from both research at university and projects at work. I started with deep convoluted neural networks in my bachelor thesis “Bootstrapping Faster R-CNN with Hard Negative Examples”. It dealt mainly with face detection using a convoluted network and hard negative mining. I continued in my graduate studies with writing a paper about the optimization of hyperparameters using a gradient based approach. Afterwards, I completed my master thesis on feature selection using a kernelized lasso. Currently, I am a PhD student at the Monash University. My areas of research are machine learning and computer vision.During my studies, I spent two years abroad with scholarships at Shanghai Jiao Tong University. There, I worked in the Microsoft Key Laboratory of Intelligent Computing and System for one year. That gave me the opportunity to gain experience in computer vision, certain techniques of digital image processing and tools like Caffe and TensorFlow. Before I left for Shanghai, I worked as a student assistant in the EU project “CRYSTAL” at the Daimler Center for Automotive IT Innovations in Berlin where I was assigned to the semantic analysis for the tool chain. Upon my return to Berlin, I joined a start-up as a student junior IT consultant with a focus on machine learning related projects. After one year and a half, I took a position as a student research assistant at Lufthansa Systems. There, I researched dynamic pricing and dynamic ancillary bundling.