Marc Ziegler Email and Phone Number

Conducting Master Thesis with focus on interpretable detection of people in 3D point clouds using stereo camera data. By integrating this detection path into the fusion algorithm and validating it against LIDAR classification, the aim of this research is to enhance the reliability and explainability of the person detection.

Implemented a safe handling component that reliably reacts to identified obstacles using a behavior tree. The handler was successfully integrated into the virtual test field of the safe.trAIn research project.

Pipeline implementation for EV benchmark analysisData Processing and AnalysisData Visualization and InterpretationEV Charging Simulation refactoring & enhancement

Machine Learning Based Used Car PricingBusiness Intelligence Visualizations (Tableau)Bug Fixing and AWS Data Base Testing (SQL)

Big Data Analytics Intern at Bosch France - Powertrain Solutions:- Pre-processing, analysis (FFT, spectrogram) and dashboard creation for audio files of electric car engines.- Representation of excel projects as json files and respective parsing in python tools.- Refactoring and enhancement of SW tools, used by applicators to automatically treat a big number of real-time measurements from test vehicles, allowing an increased maintainability and readability. This data is used for automatic validations and training of AI algorithms.- Implementation of unit tests and documentation of progress, e.g., UML diagrams- Partaking in Bosch centre for Artificial Intelligence (BCAI) courses. Including: Bayesian Optimization, Data Wrangling, Clustering, Decision Trees, NN, Regression, Statistics, Laplace Dropout, Time Series Analysis (ARIMA)

Bachelor Thesis Work on: „Analyse und Schnittstellenimplementierung von Energiesystem-Simulationsmodellen“ (engl: Analysis and Interface Implementation of Energy System Simulation Models)Abstract:Achieve the objective of a fully renewable energy system will critically depend not only on the use of regenerative energy sources, but also on a symbiotic coupling of the sectors, an intelligent networking of the system components and an expansion of the storage capacities for electrical energy. Insight into how existing and future energy systems work, as well as planning and optimizing them, will play a key role in this transformative process. Simulation models can help provide such critical insight and make an important contribution to achieving a fully decarbonised energy system. In this thesis work, current state-of-the-art simulation models for battery cells, storage systems, renewable generators, the power system, the power grid and simulation models with a holistic view of the energy system are presented and reviewed. Potential interfaces to the storage system simulation model “SimSES” as developed at TU München are described. The implementation of an interface for using mobility and consumption profiles of electric passenger cars generated by the simulation model “emobpy” developed at the German Institute for Economic Research in “SimSES” is described. Building on these profiles, the basis for an expansion of the ap- plicability of “SimSES” to charging strategies for electric vehicles is provided.

Ingenieurspraxis in der Abteilung "Absicherung Elektrischer Energiespeicher" bei EVA Fahrzeugtechnik. Tätigkeitsbereich: Testauswertung, Modifizieren & Montage, Systemadministration