Ad Fontes Society
Design implementations and spearheading the development of an MVP for an alternative healthcare platform, with the purpose of helping people finding alternative treatments
Utilizing React, Next.js, Tailwind CSS, ShadcnUI/Radix UI, Firebase, and PostgreSQL to build the platform.
Currently guiding an intern in developing their skills and contributing to the front-end part of the project.
Ad Fontes Society
Conducted initial design, UX, and UI processes, and translated Figma designs into a landing page built with
Vokalo
Designed a robust Linux-based controller for charging stations on Raspberry Pi Compute Modules, incorporating automated test environments, secure remote access, OTA updates with Mender, and a FastAPI REST API for streamlined user interaction
KMD - Clubtimiser
Contributed to the UX and UI development of KMD Clubtimiser, a Microsoft Dynamics 365-based CRM for sports clubs, optimizing the customer information dashboard for usability and enhancing user experience through HCI principles.
Master of Science (MSc) in Medialogy
My Master's thesis focused on generating user preferences based on walking routes in Aalborg, Denmark. Using a combination of Machine Learning, specifically ResNet, I developed a model to recognize and analyze Street View images, achieving over 90% accuracy in image recognition.
To model optimal walking routes, I applied the A* algorithm in a node system, allowing for pathfinding that adapted to user-defined preferences. The results demonstrated successful identification of preferred walking routes, effectively combining image recognition with weighted pathfinding to meet user needs.
All of this was implemented in a FastAPI REST API, providing a user-friendly interface for route generation and customization, the user also had the opportunity see and walk the suggested route virtually in a street view experience.
Bachelor of Science (BSc) in Medialogy
In my bachelor thesis, titled Comfortable Hand Gestures for Movement in Virtual Reality, I conducted a hand-gesture elicitation study to identify suitable gestures for locomotion control within a virtual reality environment. This project aimed to improve VR movement gestures, specifically continuous and teleportation gestures, using an elicitation-based approach.
Key research areas included defining gesture types, applying Wobbrok's study method with Morris' modifications, and minimizing legacy bias in user-generated gestures.The study involved 30 participants in both the elicitation study and a post-test, utilizing a logging system and NASA-TLX survey to assess task load.
The results indicated that gestures derived from the elicitation study had a lower task load index than industry-standard gestures, leading to discussions on the optimal number of gestures before quality declines. Additionally, I implemented software that could recognize these gestures in real-time within the virtual reality environment.