Emil Bogomolov is a research engineer in the ADASE research group at Skoltech, where he works at the frontier of machine learning and computer vision. He graduated from the department of System Analysis of the CS MSU and from the MailRu Technosphere, a foundation that combines formal analysis with hands-on engineering. An enthusiast in the field, he is also a contributor to open-source frameworks and a multiple winner of data analysis hackathons.

His research has appeared at international conferences. At WACV he published work on the segmentation and detection of human body parts and posture, and at CVPR he published on the segmentation and restoration of objects on 3D scans, areas of computer vision where accuracy directly determines what downstream systems can do.

Previously, Emil worked in the field of data analysis in retail. He was engaged in processing big data and detecting anomalies using models based on gradient boosting, experience that taught him how machine learning behaves on noisy, real-world business data rather than curated research datasets.