Time Series Forecasting Algorithms
In my PhD at Stockholm University, I work on advancing the state of the art of time series forecasting algorithms. This is a foundational machine learning challenge, which can be applied in different application scenarios.
Machine Learning Explainability
The secondary focus of my PhD thesis is machine learning explainability, specifically for time series forecasting tasks. Explainability helps end-users understand the decision-making of machine learning models.
Digital Twins for Smart Buildings
My PhD is conducted in collaboration with Atrium Ljungberg on the topic of forecasting and explainability in digital twins. Smart buildings are the prime application case of the project.
Production Line Optimization
Currently, I am working on a project with Glapor on production line optimization. This project uses time series analysis techniques to improve production efficiency and identify faults in the current system.
AI for Electric Vehicle Chargers
I worked at alpitronic on company-owned electric vehicle charger system log data, implementing text processing and data mining techniques for charging anomaly detection to improve the system.
ML for Computational Neuroscience
During my research internship at OIST, I implemented a 3D image segmentation machine learning pipeline with the goal of classifying Purkinje cells into dendrites and spines.
