Andrii P.

Experienced in: 1. Computer vision • C++, Python, OpenCV, CUDA, Git, Linux, Qt, Boost, OpenGl, PCL, Strong math background, Neural Networks - road segmentation for unmanned vehicles (ENet, Caffe, OpenCV, C++, Linux) - car tracking (Yolo v3, OpenCV, C++, Linux) - wagon number identification (Yolo v4, Python) - implementation of real time 360°/perspective camera transformation on Cuda (C++, Cuda, OpenCV, Linux, Jetson Nano) - distance calculation to point on 2D camera frame (C++, OpenCV, Linux) - automate grading system for handwritten answer sheets (computer vision part, OpenCV, Java, Android Key stack: Linux, C++ (Qt), Python, Java, OpenCV, Yolo (darknet) 2. Machine Learning Machine learning research projects in the following domains: - person segmentation (ModNet, RVM, TDNet, UCTransNet, XMem etc.) - image inpainting (Pen-Net, Deepfillv2, Shift-Net, ViNet etc.) - image upscale (RDN, RRDN, Stable Diffusion, ISR etc.) - image relighting (Total Relighting, DPR, RelightNet etc.) - road segmentation for unmanned vehicles (ENet, Caffe, OpenCV, C++, Linux) - car tracking (Yolo v3, OpenCV, C++, Linux) - wagon number identification (Yolo v4, Python) - implementation of real time 360°/perspective camera transformation on Cuda (C++, Cuda, OpenCV, Linux, Jetson Nano) - distance calculation to point on 2D camera frame (C++, OpenCV, Linux) - automate grading system for handwritten answer sheets (computer vision part, OpenCV, Java - Android, IOS - Swift) Key stack: Linux, Python, Pytorch, Tensorflow, OpenCV, Pillow, Numpy, C++, CUDA, Darknet, SegNet 3. Robotics and Embedded development: - OCPP Protocol, Linux, Modbus, Raspberry Pi, CAN; -ROS Robot operating system; - Skilled in SLAM, localization, mapping - Experienced in path planning algorithms, obstacle avoidance, holonomic, and non-holonomic motion planning, trajectory planning for robotics arms; - Used to work with Bayesian/Kalman filters, and sensor fusion (LiDAR, IMU, Visual, Odometry, Radar, GPS). 4. Android development (Kotlin, Java, Android Studio, Eclipse, Firebase). Has expert colleagues in: • .Net Framework (C#, VB.Net, ASP.Net, .Net Core, WPF, UWP,WCF, ADO.Net) • Java (j2se, j2ee, servlets, java beans, Maven) • JavaScript (Node.JS, Express.js, Vue.js, Element.js, Angular.js, D3.js) • C++ (TCP/IP, HTTP, HTTPS, WebSocket, Modbus) • Python (MAVLink, WebSocket) • Step7 (S7 Communication, OCPP, Modbus, CANOpen, ProfiNet) Database • PostgreSQL • MySQL • MongoDB • Microsoft SQL • Oracle Database • Neo4J Software development for mobile platforms • Crossplatform React Native, Flutter, Xamarin, • Android (Kotlin, Java, Android Studio, Eclipse) • iOS (Objective C, Swift) Mobile apps development: • Crossplatform: Futter, React Native, Xamarin. • Android (Java, Kotlin) • iOS (Objective C, Swift) 1. Native Development - Kotlin/Java - Swift / Objective-C - iOS/macOS/tvOS/watchOS - Firebase, CloudKit, Coredata 2. Cross-Platform and Hybrid App Development - React Native/React - Flutter / Dart - Xamarin.iOS / Xamarin.Android / Xamarin.Forms tech stack ● Android Studio, Gradle, Kotlin DSL, KSP ● Kotlin, Java programming languages ● AndroidX, Android Jetpack libraries, Android Architecture Components ● Jetpack Compose ● Material Design Components ● Clean Architecture, SOLID design principles ● MVVM, MVI, GoF design patterns ● Modularization (multi-module projects) ● Kotlin Coroutines + Flow, RxJava, RxBinding ● REST API / Networking - OkHttp, Retrofit 2, Socket IO ● Room Database, SQLite, Datastore ● Kotlinx Serialization, Protobuf, Moshi, Gson ● Dependency Injection (Hilt, Dagger 2, Koin) ● Git ● Firebase Products, Google Cloud APIs, HMS Services ● Admob, Google Play Billing Library (in-app purchases), Samsung/Huawei IAP ● Unit / Instrumented (UI) tests ● Agile Scrum development methodology ● CI/CD (GitHub Actions) AR/VR: Vuforia ARkit/ARcore/AR Foundation Wikitude Oculus Integration OpenXR XR Interaction toolkit VR Walkthrough UltimateXR VR Interaction Framework Hardware expert: • Nvidia Jetson Nano, TX2, Xavier; • Raspberry Pi; • Arduino, STM32; • Depth cameras Intel Realsense d435i , Zed Sterelabs. • Lidars, Radars. Charging stations for the Electric Vehicles development software for the managing stations and networks (server and user applications): • C#, SQL, PostgreSQL, .Net Core, REST Api, WebSockets • OCPP Protocol, Linux, Modbus, Raspberry Pi Software development • .Net Framework (C#, VB.Net, ASP.Net, .Net Core, WPF, UWP,WCF, ADO.Net) • Java (j2se, j2ee, servlets, java beans, Maven) • JavaScript (Node.JS, Express.js, Vue.js, Element.js, Angular.js, D3.js) • C++ (TCP/IP, HTTP, HTTPS, WebSocket, Modbus) • Python (MAVLink, WebSocket) • Step7 (S7 Communication, OCPP, Modbus, CANOpen, ProfiNet) Database • PostgreSQL • MySQL • MongoDB • Microsoft SQL • Oracle Database • Neo4J