I am broadly interested in probabilistic modeling, generative machine learning, and efficient inference techniques. For my master’s thesis, I researched on developing variational inference techniques for non-linear SDEs. Recently, my work has focused on sequential decision-making models that need computationally efficient and well-calibrated uncertainty.
I graduated from Aalto University, Finland, with a Master's in Machine Learning, Data Science and Artificial Intelligence as major and Mathematics as minor (2019-2021).
In 2021-2022, alongside Aalto University, I also worked with SpectacularAI as a consultant for an electronics firm developing methods to integrate uncertainty in their deep learning models, making them robust. During 2016-2019, I worked in the R&D team of TomTom, responsible for devising, developing, and bringing into production innovative new technologies. My work mainly revolved around machine learning, image processing, and automation, focusing on revolutionizing map data.