![VH](https://d2abrqas732254.cloudfront.net/images/specialists/88e861f6866ca45d7a0e95f98b993fe3e1d657a1.png)
English:
Upper Intermediate
Vlad H.
Vetted by YouTeam
Ukraine
UTC +02:00
Ukraine/Kyiv
English:
Upper Intermediate
C++ Embedded engineer
Want to hire this engineer?
Check if Vlad is availableExpertise
Years of commercial development experience
8 years of experience
Core technologies
Project Highlights
Pixpie
Feb `21 - Present
4 years
Improving webp compression ratio.
Responsibilities & achievements
● Implemented quite silly WebP progressive mode; ● Applying compression ratio and / or speed optimizations depending on input conditions.
Smart Heater
IoT-enabled smart heater.
Responsibilities & achievements
● Smart heater for smart home; supports WiFi, Bluetooth and ZigBee; ● Implementing WiFi-enabled board firmware using C and esp8266 rtos sdk; ● Implementing UART-based protocol for communication with heater core; ● Making draft version of client app using Flutter.
BLE Location
High-precision beacon location system.
Responsibilities & achievements
● Calculates precise location of any device (or object with beacon attached); ● Schematics and firmware done on customer side; ● Implemented simple desktop client app (Python, PySide2).
Emotion Tracking
Raspberry pi-based solution for driver's emotion detection.
Responsibilities & achievements
● Analyzing driver state, detects drowsiness, eye closure, head pose, maps facial actions to emotions; ● Implemented on Raspberry Pi, runs in 5-10 fps; ● Improving current solution by training new models (PyTorch, python, implementing C++ version on Raspberry Pi for better performance and memory footprint); ● Creating NodeJS addon to enable communication with Electron-based frontend.
QC
Web-based home-planning project.
Responsibilities & achievements
● Improving 3d team performance by creating blender addons (python); ● Implemented experimental real-time rendering solution using UE4 (c++, blueprints); ● Implemented side project for automatic solar panel placement using aerial images (python3, pytorch, convolutional neural networks, opencv-python, asp.net).
AV1 encoder optimization
Speeding up encoding at certain modes.
Responsibilities & achievements
● Optimizations applied in certain encoder modes; ● Implemented using AVX / AVX2, where it could be applied well; As a result, speed improvement gained, from 5 to 30%, depending on encoder settings and resolution.
Toolook
Image and video "neural styling".
Responsibilities & achievements
● Implemented using Torch Lua bindings and convolutional neural networks (VGG19, Resnet variants); ● Made both image and video stylization options; ● Video stylizations sped up 2x by implementing ffmpeg filter and exposing Torch C api to it.
T360
Autonomous jetson tx2-based robot.
Responsibilities & achievements
● Implemented real-time 360 degrees image stitching by transforming stream from 2 fisheye lenses; ● Integrated it into current solution as ffmpeg filter; ● On top of it, neural networks were applied to detect pedestrians; ● Made experimental SLAM version from scratch using C; ● Ported everything to Jetson TX2, made performance optimization.
Education
Higher education in Computer Science
Agency
10-50
GMT+2
Kharkiv/Ukraine
Core Expertise
Industries
Banking & Finance, Information services & Technologies, Internet & Telecom, Healthcare & Medicine, Safety & Security, Cybersecurity & Data Protection, Branding, design, web development, SaaS, Uberization of Industries
Want to hire this engineer?
Check if Vlad is available