Building proof of concepts relating to vehicle behavior in order to propose gainful project ideas.

Title: Keyword detection using machine learning within automotive environment. Built a multistep pipeline to load and augment gigabytes of audio data, extract features, and perform exhaustive architecture- and parameter tuning according to specified configurations. The project successfully achieved multiple well performing models within the automotive environment.Developed a framework for the distributed collection of labeled data and a demonstration system for real-time audio recording, feature extraction, and model prediction using Python and Flask.

Designed and developed a Python package to promote large-scale design exploration capabilities using distributed and scalable data infrastructure augmented with artificial intelligence for DEFAINE (Design Exploration Framework based on AI for froNt-loaded Engineering). See more at (Swedish): https://www.chalmers.se/sv/projekt/Sidor/DEFAINE-QDesign-Exploration-Framework-based-onAI-for.aspx

Saved 100+ hours annually by designing a Python package to automatically and intelligently send calculation tasks from different operating systems to their HPC-cluster. Identified structure vulnerabilities by developing an interpolation tool in Python to analyze load differences between various 3D-meshes.Worked in Azure DevOps with Python and Jupyter-Notebook.

Planned and held practices for classes of up to 8 people.

Developed a program to standardize and facilitate the planning and construction of environmental facilities.