Andrey Ustyuzhanin

Director of AI/ML research at Acronis, visiting research professor at NUS, Singapore. His research's primary priority is designing new Machine Learning methods and using them to solve challenging scientific enigmas, thus improving the fundamental understanding of our world. Currently, he focuses on developing strategies for searching for new materials in the Institute of Functional Intelligent Materials (IFIM). His current research focus is developing fast simulation models and inverse design algorithms for materials that exhibit unique properties. 

Before joining IFIM, he led a group of computer scientists collaborating with several particle physics experiments: LHCb, SHiP, OPERA, CRAYFIS, and SND. Amongst the projects he has been working on are efficiency LHCb projects on improving online triggers and speeding up BDT-based online data processing. He participated in designing custom convolutional neural networks for processing tracks of muon-like particles on smartphone cameras—the development of the algorithm for tracking optical fiber detectors and emulsion cloud chambers in scintillators.

Discovering the more profound truth about the Universe by applying data analysis methods is the primary source of inspiration in Andrey's lifelong journey. Andrey is a co-author of the course on Machine Learning aimed at solving Particle Physics challenges at Coursera and organizer of the annual international summer schools following similar topics.