I am broadly interested in machine learning and computer vision. Particularly, my current projects are mostly concentrated around Bayesian optimization and practical methods using deep learning. I especially enjoy when combined knowledge from different fields resonates. Prior to ETH, I have graduated from MIPT and Skoltech – places with great people and great courses! At Skoltech, I worked on DL methods for weakly-supervised semantic segmentation under the supervision of Victor Lempitsky and interned at Columbia University under the co-supervision of Hod Lipson. I have also interned at Yandex, where I worked on DL based precipitation nowcasting.
