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Solving the last mile problem. Built a robot delivery startup. Supported by EIT Urban Mobility, Future City Accelerator, Telekom Hubraum & others.

Entrepreneur First brings together extraordinary people to build startups from scratch in London, Singapore, Berlin, Toronto, Paris and Bangalore. EF funds individuals and helps build co-founding teams, develop ideas, and accelerate through fundraising from the world's best investors.For more information about Entrepreneur First, check out www.joinef.com.

Advised by Prof. Katerina Fragkiadaki (Machine Learning Department)► Conducted research for my master thesis: "Graph Neural Networks for Scene Dynamics Prediction and Robotic Manipulation"► I worked on computer vision, graph neural networks, robotic manipulation and deep reinforcement learning.

University research project in cooperation with the Interactive Systems Labs (ISL) at KIT► Project: DeepQA - A Question Answering System based on recurrent neural networks.► Tools: PyTorch; Dataset: "QA bAbI tasks dataset" (Facebook "The bAbI project")► GitHub: https://github.com/pwieler/DeepQA► Implemented different recurrent architectures (e.g. LSTM, GRU, etc.).

IAR - Institute for Anthropomatics and Robotics in cooperation with FZI (Forschungszentrum Informatik)► Project: Cooperative Interacting Automobiles (DFG-Project), https://www.coincar.de/#/- Assisted in different areas: Urban Traffic Simulation (Gazebo, SUMO, ROS), Object-Detection (TensorFlow on Android)

University research project in cooperation with Fraunhofer IOSB► Project: Synthesizing realistic 3D face images using generative adversarial networks (GANs). ► Implemented different GAN architectures (e.g. BEGAN, CycleGAN, StarGAN).► Tools: TensorFlow, Keras; Dataset: "300W-LP (300 Faces in the-Wild across large Poses)"

► Bachelor-Thesis @Augmented Reality GroupThesis: “Evaluation and Optimization of Visual SLAM in Traffic Scenarios”► Internships in several R&D divisions:• Augmented Reality Group: - Implemented a vision-based object detection of vehicles (C++, OpenCV); - Implemented a visual SLAM (LSD-SLAM) to track the trajectory of a vehicle from images obtained by a monocular camera (C++, ROS, MATLAB).• Autonomous Driving Group: - Worked in the testing team of a self-driving car. Helped improving the visualization of sensor information in the vehicle during test drives.• Driver Observation & Driver State Detection: - Implemented a system to track the driver's gaze direction by tracking his movement with head- & eye-trackers.• Project & Team Leader in the student project "Magic Comfort Control" with a group of 7 students.- Developed a person-recognition system for person-dependent comfort settings in a real vehicle (Mercedes-Benz A-Class, CAN-bus, Kinect).

► Autonomous Driving Group: Worked in the testing team of a self-driving car. Helped improving the visualization of sensor information in the vehicle during test drives.