I hold a Bachelor's degree in Electrical Engineering, specializing in Power Engineering and Control, and a Master's in Information and Communication Technologies. Currently, I am in the final year of my PhD studies in Information and Communication Technologies and work as a Young Researcher at the Jožef Stefan Institute in Ljubljana.

My research lies at the intersection of machine learning and structured output prediction, with a strong focus on developing Bayesian and interpretable models. I am particularly interested in advancing methods that balance predictive performance with transparency, enabling models to make accurate and explainable decisions in complex settings. Over the course of my academic and professional journey, I have built solid expertise in both predictive and generative AI, as well as in stochastic modeling. I have experience working with a range of machine learning methods, with a focus on developing robust models that generalize well and align with real-world constraints. I have applied my research in various domains such as Computer science, Material science, and Economics.

As a researcher, I value clarity, rigor, and applicability, and I am motivated by the impact machine learning can have in science and industry. I am always looking for opportunities to collaborate on innovative projects and to bridge the gap between cutting-edge research and practical solutions.