Andrey Pavlenko
Staff SW Engineer at Arm
Cambridge, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolAndrey Pavlenko is a Staff Software Engineer with two decades of experience building and leading cross-geography teams to deliver bit-accurate C/C++ models and high-performance imaging software across Windows, Linux and Android. Based in Cambridge, he has driven ISP and system-level modeling at Arm, improving CI, development processes and producing public CPU/GPU-accelerated models such as the Mali-C71AE SW model. His background includes deep contributions to OpenCV/OpenVX—fixing compatibility and build issues and adding image-processing tests—highlighting a strong open-source pedigree in computer vision. Andrey combines hands-on optimization (C++11, OpenCL, OpenCL/OpenVX, OpenCV) with project leadership, from scoping and customer communication to hiring and CI automation. Fluent in English and experienced across tooling ecosystems from Visual Studio to GNU build systems, he thrives in fast, multitasking environments. Notably, he pairs low-level systems expertise with a long history of shipping cross-platform developer tooling and demo applications for Android and embedded targets.
12 years of coding experience
21 years of employment as a software developer
Master, Computer Science, Master, Computer Science at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Russian, English
Github Skills (6)
computer-vision10
opencv10
c-language10
cprogramming-language10
image-processing10
cpp8
Programming languages (3)
Github contributions (5)
opencv/opencv
Nov 2016 - Dec 2016
Open Source Computer Vision Library
Role in this project:
Software Engineer
Software EngineerContributions:5 releases, 17 commits, 20 PRs in 29 days
Contributions summary:Andrey primarily focused on improving the OpenVX implementation within the OpenCV library. Their work involved fixing build issues related to OpenVX version 1.0.1 and C++03 compatibility. They also addressed compiler warnings by adding and removing pragmas and made adjustments to the IVX wrapper library. Furthermore, the user implemented a test comparing OpenCV's Canny edge detection with an OpenVX implementation and added single-plane image handling improvements.
pythonvisiondeep-learningc-plus-pluscomputer-vision
apavlenko/vmf
Nov 2015 - Jun 2016
Contributions:64 PRs, 267 pushes, 51 branches in 6 months
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