"Engineers are usually trained in a very fixed area. When you’re able to think about all of these disciplines together, you kind of think differently and can dream of much crazier things and how they might work. I think that’s really an important thing for the world. That’s how we make progress.”
June 2023 - Present, Heilbronn
As the first AI Engineer at the IPAI, I am building up the technical AI expertise in the upcoming largest EU AI ecosystem Heilbronn together with our local partners and represent appliedAI in various technical workshops, events, and our technical projects together with our industry partners. Besides that I am working on several full-stack Machine Learning projects with an additional focus on LLMs.
Sept. 2022 - Feb. 2022, Munich
Machine Learning for Sensor Fusion in Localization. Data-based approaches using situational information to estimate the trustworthyness of sensors for localization by inventing and applying a custom ML architecture for late sensor fusion.
Jan. 2022 - July 2022, Munich
Very proud to have left the Junior level behind. Still working in the Engineering department covering a wide variety of use-cases together with our partners. Personal highlight for me was the KI Transfer+ program by the Bavarian State Ministry for Digital Affairs, where I supported with my technical expertise and also gave workshops on Machine Learning for the companies. Working on various AI projects together with our industry partners to generate value with AI solutions.
Sept. 2020 - Dec. 2021, Munich
Europe’s largest non-profit initiative for the application of artificial intelligence technology.
Part of UnternehmerTUM, Europe's leading center for start-up and innovation with more than 50 high-growth technology start-ups per year and its unique range of services.
Oct. 2015 - July 2020, Ingolstadt
Dual studies program at Audi AG, a training program in Mechatronics Engineering and Bachelor's degree. All combined with project work during semester vacations.
Major academic course highlights so far:
Feb. 2020 - June 2020, Ingolstadt
Real-data-based development of driver behavior models (driver interventions in vehicle dynamics in response to changing vehicle environment) in near-collision situations.
July 2019 - Sept. 2019, Ingolstadt
Synchronization of Real Time Kinematic Data (RTK) with training and test data sets for the evaluation of image processing algorithms for scene reconstruction and localization of camera positions
July 2017 - Sept. 2017, Ingolstadt
Concept development, designing and programming of a parking lot terminal for Audi Piloted Parking using HTML, CSS, JQuery and a websocket connection.
Feb. 2017 - March 2017, Ingolstadt
Preparation of an automotive concept for a water detection technique based on a conductive lacquer.
Feb. 2016 - July 2016, Ingolstadt
Conceptional design and implementation of an Automated Guided Vehicle used for logistics.
Aug. 2018 - Jan. 2019, Barcelona
Working as a Web Developer in an Agile Development Developer Team and launching ByBus - a bus on demand mobility solution. Building the Web Client for the application with real - time situation tracking allowing a fast overview about the status of the service.
Sept. 2018 - Oct. 2018, Ingolstadt
Due to the new structure in the organization removing the chiefs, I was again working as a developer in the Autonomous Systems team.
While the software was almost finished for first test runs, we were mainly working on the hardware of the car. Here we needed to connect the DrivePx with all the sensors and actuators to actually get our achievements from our simulation on the street.
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Sept. 2017 - Sept. 2018, Ingolstadt
Autonomous Systems is responsible for transforming the last years electric car into an autonomous vehicle by upgrading the car with sensor, actuators, processing units and intelligence.
As a Chief of the department I was leading a group of passionate students all interested in the field of Autonomous Driving.
Here is a short summary of what we achieved as team of ~8 students:
https://s3-us-west-2.amazonaws.com/secure.notion-static.com/8580a33f-c4ff-4877-baa7-b6a7272d5b25/output.mp4
March 2017 - Sept. 2017, Ingolstadt
Responsible for sensing the environment using automotive certified GMSL cameras. After receiving the bounding boxes of the neural net, a top view is calculated preparing the data for mapping.
Oct. 2024, Abu Dhabi
In our work, we propose a novel data-driven but provably bounded sensor fusion and apply it to mobile robotic localization. In extensive experiments using an autonomous driving test vehicle, we show that our fusion method outperforms other safe fusion approaches.
https://www.cs.cit.tum.de/daml/sadf/
Nov. 2022, Munich
This patent describes a device for determining the state of a vehicle by evaluating multiple hypotheses about its condition. Specifically, the device is designed to generate K different state hypotheses (K > 1) related to the vehicle's condition. It also calculates a feature vector that describes the vehicle's driving situation. Using a machine learning unit, the device determines K weights for the respective hypotheses based on this feature vector. Finally, the device combines the K hypotheses into a single, merged state hypothesis reflecting the vehicle's overall condition.
https://register.dpma.de/DPMAregister/pat/register?AKZ=1020221312976