Biography

A big fan of coding and physics, Dino earned a masters in Computational Physics at Faculty of Science Split, Croatia, on the topic of linear feature detection in astronomical images. Having re-analyzed the entire Sloan Digital Sky Survey (SDSS) ~16TB large image dataset he discovered his passion for Big Data and related image analysis problems. As a graduate student at University of Washington, Dino works on Large Synoptic Survey Telescope (LSST) Data Management code, adding support for cloud services and executing Science Pipelines in the cloud. To various different extent he is also involved in other projects such as image differencing, kernel based moving object detection (KBMOD) and deblending.