I’m a Ph.D. student in the Department of Information, Risk and Operation Management at UT Austin, advised by Prof. Mingyuan Zhou. My research is in deep Bayesian learning using adversarial methods and variational inference. I hold an M.Sc. and B.Sc. in Computer Science from the Faculty of Computer and Information Science at the University of Ljubljana, where I worked on using Gaussian processes for for multivariate count data with Prof. Erik Štrumbelj. Before that, during my B.Sc, I worked with Prof. Matej Kristan on unsupervised image segmentation. Before my Ph.D. I worked on applying machine learning to different domains. I spent a summer at Stanford University, working with Prof. Jure Leskovec on applying NLP to extract protein-protein interactions from the scientific literature, and as a data scientist at Zemanta and Salviol preventing fraud in native advertising and insurance claims, respectively. For more details, see my CV.
|Dec 18, 2019||Welcome to my new personal website!|
|Feb 24, 2017||3rd place at a Kaggle-like competition featured in Science: Predicting human olfactory perception from chemical features of odor molecules.|
|Jun 10, 2016||Awarded a silver medal at the 1st Kangaroo Math Competition for Slovenian college students.|
|Mar 28, 2016||A regularization-based approach for unsupervised image segmentation was published in the Journal of Electrical Engineering and Computer Science, which contains my B.Sc. work, previously presented at the ERK conference.|
|Jan 4, 2016||Awarded the Dean’s Commendation for Academic Excellence, given to the students with the highest GPA each year.|
|Dec 28, 2015||Presented the paper Learning From Microarray Gene Expression Data at the Information Society Conference. Interestingly, genes predicting one cancer were also predictive of other cancers in different data sets.|