Roman Golovanov

Roman Golovanov's work experience includes roles at various companies in the field of computer vision and software development.

From 2009 to 2018, they worked at CQG, Inc. in roles such as Senior Expert-Developer and Technical Team Lead, where they developed algorithms and tools for market analysis and data processing.

In 2014, they worked as a Computer Vision Researcher at ZelProm-Telecom, focusing on developing navigation systems for unmanned aerial vehicles (UAVs) using Computer Vision algorithms.

From 2015 to 2019, they were an Associate Professor at the National Research University of Electronic Technology (MIET), teaching courses on mathematical analysis, image processing, and computer vision.

In 2018, they became the Lead Computer Vision Scientist at ELVEES RnD Center, JSC, leading a team of researchers and engineers and focusing on the development of computer vision algorithms.

Currently, they are employed at Varjo as a Principal Computer Vision Engineer, leading a team of experts in tracking technologies and overseeing roadmap planning, resource allocation, and external collaborations.

Throughout their career, Roman has demonstrated expertise in computer vision, machine learning, sensor fusion, embedded systems, and software architecture. Roman has also been involved in research, productization, patenting, and academic mentoring.

Roman Golovanov obtained a Doctor of Philosophy (Ph.D.) degree in Physics and Mathematics from the National Research University of Electronic Technology (MIET) in 2014. Prior to that, they earned a Master of Computer and Information Technology degree in Mathematics from the same university between 2005 and 2011.

In addition to their formal education, Roman has obtained several certifications. These include Coaching Skills for Leaders and Managers from LinkedIn (year not specified), Hands-On PyTorch Machine Learning from LinkedIn in 2022, MLOps Essentials: Model Development and Integration from LinkedIn in 2022, Machine Learning Engineering for Production (MLOps) Specialization from DeepLearning.AI in 2021, Machine Learning from Stanford Online in 2021, Functional Programming Haskell from Stepik in 2020, C++ from Brainbench in 2011, and C++ Fundamentals from Brainbench in 2011. The specific months of obtaining the certifications are not provided.