Position: Java Developer
Category: Java
English level: upper
Years of experience: 4


Notable Projects:  

PromptSmart – Studio Edition, July 2018 - July 2020
Position: Junior-Middle Java Developer
Accomplishments:
 - Smooth text scrolling
 - Integrated MVP architecture
 - Fixed recognition latency
 - Rich UI implementation
 - Implemented structure and logic for complicated script editor to handle and process UI events
 - Reduced CPU load from 90% to less then 15%
 - Developed installation ways for Windows and Mac OS with ability to update application
 - Developed system of user`s files management inside application
 - Implemented authentication and registering user in application
 - Implemented files and setting synchronization with server
 - Integrated MQTT for real-time editor updating

OpenLegacy, January 2019 - March 2019
Position: Junior Java Developer
Accomplishments:
 - Implemented editor for license files contained in created projects, and same viewer for OpenLegacy IDE license
 - Implemented creating some projects with configurations specified in YML file instead of “hard-coded values”, fixed editor for configuration files of these projects
 - Added installation of additional library to local Maven repository for some kind of projects

Chk-In Cam ConeC, August 2020 - July 2022
Position: Middle-Senior Java Developer
Accomplishments:
 - Implemented all the REST API for using a separate front-end instead of MVC.
 - Implemented REST admin API.
 - Optimized work of devices map admin page by server-side clustering and filtering by viewport
 - Implemented REST API and JWT authentication for Hearing Assist back-end
 - Created IP-cameras emulation server app that streams RTSP video from video files
 - Set up building Docker image for fall recognition server (Python app) with access to GPUs
 - Implemented concept of desktop fall detector app (PyQT).
 - Implemented drawing polygons on video overlay for configuring regions of interest for cameras (Python Linux desktop and front-end).
 - Changed workflow to allow using the common recognition server that can be accessed by each user, implemented separate authorization flow for recognition server (Java web app and Python app).
 - Implemented load balancing system for fall recognition servers
 - Improved fall detection algorithm (Python).
 - Optimized work of threads which are responsible for reading and processing video stream from ip-camera (Python).
 - R&D on human detection and action recognition on video