Projects
Head of Process Automation & Developer
During my career as a computer scientist, I have been involved in many innovative automated systems that redefine convenience, efficiency, and sustainability.
All began with an internship at the IAV, where I contributed to the creation of a groundbreaking system — the Concierge Service. This pioneering initiative empowered vehicles to autonomously perform multiple tasks at parking spaces. It enabled cars to handle activities such as car maintenance, finding parking spaces, and even executing repairs fully autonomously.
During my master thesis, I architected real-time optimization algorithms in C++ to make trains more energy-efficient. I focused on crafting algorithms aimed at energy efficiency by calculating the optimal driving strategies in real-time - an solution that holds immense promise for sustainable transportation solutions.
As a software engenier I started a job at STTech what further fueled my passion for automated systems as I had the chance in developing autonomous cleaning robots build for the demands of expansive spaces like supermarkets and warehouses and working on autonomous car driving solutions.
After 1.5 years at STTech, serving as the head of process automation, my focus was to revolutionize the claim handling processes for insurance companies, particularly within the domain of dentist invoices. This domain allowed me to leverage automation to enhance efficiency, accuracy, and customer satisfaction.
DALL-E 3 generated image based on my career
Claim Automation
Demo: Left - The client side SwiftUI App. Right - Insurance App for an optimised emplyee experience
Leading the Process Automation Team
Experience streamlined insurance claim handling. Our innovative application showcases a split-screen demo. On one side, clients effortlessly scan and submit documents via a native iOS app. On the other, insurance employees access a tool for manual processing, swiftly addressing OCR errors or client queries.
Watch as automated processing seamlessly transforms submissions into completed tasks within the insurance system. Witness the application's adaptability as intentional modifications trigger a smooth transition to manual intervention, ensuring accurate assessments.
This demo highlights our application's powers with routine tasks while seamlessly accommodating manual intervention when needed.
Set
iOS UIKit App for Playing Set
Driven by my passion for the card game Set, I developed an iOS app to further enhance my skills in iOS app development.
This comprehensive app showcases my coding proficiency through various details, including:
- Creating an aesthetically interface using UIKit and Swift
- Implementing unique card designs with custom shapes created using bezier paths
- Developing robust game logic with automatic set detection in Swift
The app offers three distinct play modes: single-player, multiplayer, and the option to challenge an AI opponent. Notably, it intelligently determines whether the selected cards form a Set and features a user-friendly indicator – a green background on the "3 More Cards" button – signaling a safe time to proceed when no Sets are present on the table.
This project reflects not only my dedication to mastering iOS app development but also my commitment to delivering a polished and enjoyable user experience.
Set executed in a Swift-Playground
Throw Optimization
Optimizing the throwing strength
During my master thesis at Siemens Mobility, I came across a series of algorithmic challenges, particularly focusing here on the preparation work for my closed-source master thesis, which is protected for five years.
The core preparation task involved calculating the optimal throwing strength of a ball for a given destination in real-time. The visible outcome is a remarkable simulation demonstrating the trajectory of a ball over time, precisely executed with the optimal strength. Noteworthy is the efficiency of the computation – accomplished in less than 20ms enabling real-time adjustments to the start position. In contrast the brute force approach, renders real-time performance unattainable with multiple seconds.
While the specific details of the master thesis remain confidential, its overarching goal was groundbreaking – aimed at reducing energy consumption in trains. The focus was on the development of a real-time algorithm to optimize driving strategies based on the timetable and track constraints, thereby contributing to the broader initiative of sustainable and efficient transportation systems.
Be[e] Alive
iOS SwiftUI app for optimizing insect food
In the face of climate change and escalating urbanization, pollinators such as bees encounter challenges in locating abundant floral resources. So I invented an App — an innovative solution designed to assist cities and avid gardeners in selecting the optimal assortment of flowers throughout the year.
Key Features:
- Intelligent Plant Selection: The app uses SwiftUI for an intuitive interface that simplifies the process of choosing the right mix of flowers, fostering a continuous bloom.
- Connected to a Netcup-Hosted API: Leveraging a self-created API, the app seamlessly integrates with a growing flower database. Although the database is a work in progress, the app is on the edge of being released to the App Store.
- Functionalities: The app boasts a robust set of features, including a plant search, a calendar for optimal planting times, and an overview page for quick reference.
While the database is currently in development, the vision is to populate it comprehensively with a diverse array of flowers, ensuring a rich and ever-expanding resource for users.
SwiftUI App recorded on an iPhone.
LinkedIn Assessment
Skill Training Web App: Reinventing Skill Assessments
I developed an innovative web application to enhance skill training, inspired by LinkedIn's former skill assessments. The app converts GitHub-crawled markdown files into JSON data, creating a dynamic question pool.
Key Features:
- MongoDB Integration: Seamlessly connected to MongoDB, storing user progress and results for a personalized learning experience.
- Adaptive Questioning: Utilizes a smart algorithm to present new questions, revisit incorrect answers, and strengthen understanding by revisiting correctly answered questions.
- LinkedIn-inspired Interface: Recreates the engaging skill assessment experience, for continuous skill development.