Highly-motivated employee with desire to take on new challenges. Strong work ethic, adaptability, and exceptional interpersonal skills. Adept at working effectively unsupervised and quickly mastering new skills.
Overview
5
5
years of professional experience
Work History
Junior Sensor Simulation Expert
DB InfraGO GmbH
Berlin
07.2023 - Current
Developing and validate high-fidelity digital twins of perception sensors, focusing on camera and LiDAR modalities.
Conducting simulation-based safety verification against railway standards and norms.
Integrating physically realistic models in NVIDIA Omniverse software for virtual testing scenarios.
Researching state-of-the-art methods in sensor simulation and contributed to ongoing innovation efforts.
Sensor Simulation Intern
DB Netz AG
Berlin
10.2022 - 06.2023
Built virtual representations of optical sensors in Omniverse with physics-based realism.
Automated and optimized sensor placement and evaluation within digital railway environments.
Supported digital engineering workflows and collaborated across simulation and safety teams.
LiDAR Data Labeler
LIANGDAO GmbH
Berlin
03.2022 - 06.2022
Labeled and validated 3D point cloud data for object detection and semantic segmentation tasks.
Participated in software testing cycles for labeling tools used in autonomous driving development.
Master Thesis
Technische Universität Berlin
Berlin
04.2022 - 02.2023
Title: Development of an algorithm to to find relevant plants along a railway
Grade: 1.0
Project: Object Detection Models Evaluation
Technische Universität Berlin
Berlin
10.2021 - 03.2022
Compared 2D/3D object detectors based on A2D2 dataset, evaluated metrics e.g., precision-recall, AP, F1 score for autonomous perception.
Project: Battery Design & Simulation
Technische Universität Berlin
Berlin
10.2020 - 03.2021
Applied Kalman filter and balancing algorithms to reduce SOC variance across battery packs below 5%.
Project: Diesel Engine Modeling
Technische Universität Berlin
Berlin
10.2020 - 03.2021
Built and optimized engine simulation models using statistical tests (e.g., D-opt, T-test).