I am a master’s student (M.Sc.) in Data Science at Uppsala University, with a prior Bachelor’s degree (B.Sc.) in Software Engineering & Management from the University of Gothenburg, in Sweden. The thesis topic explored in Software Engineering & Management was “Exploring Metrics for Safety and Reliability Assessment in an Automotive Emergency Braking Perception System: A Case Study”.

My interests are in the field of Machine Learning, and Deep Learning, with a deeper interest developing in the paradigm of Federated Machine Learning, allowing de-centralized model training from multiple clients in a privacy-enhanced method, where data does not need to be transferred, but occurs locally.

• I have previously worked in a diverse range of projects, primarily in full-stack web development, data analysis, feature engineering, and ML-powered application development.

• I have contributed in designing a data-intensive stock sentiment prediction application Marketpulse using Django and Tensorflow.
  • using an explainable-AI framework (LIME)
  • featuring re-training possibilities with an administrator-dashboard for versioning of models currently active on the application, and adding new models or replacing them for use on the production side.

• Worked with fine-tuning of Large Language Models in applications of telecommunication products and specs-information retrieval at Ericsson R&D.

• Member of Development Division at Uppsala AI Society from August 2025.

Skills and Frameworks

I hold experience in software development in Python, Java, JavaScript, and HTML/CSS. In a diverse range of team-based environments, I have applied software development practices, particularly Agile methodologies like Kanban and Scrum.