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.