Eyad Arshad
Computer Vision Engineer | C++ Qt6 Desktop Apps | AI Systems
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Title: ERP System Utilisoft: Offline Business Management Suite (C++ Qt6)
Description: Designed an offline-first desktop ERP suite built in C++ and Qt6 to handle inventory, POS sales, and analytics logging.
Modular C++ Architecture: Built a modular desktop system featuring inventory management, sales logging, and vendor tracking.
Database & Access Control: Integrated SQLite/MySQL pipelines with a secure 3-tier Role-Based Access Control (RBAC) system.
Analytical Dashboard: Designed interactive analytical charts utilizing Qt Charts for instant offline business metrics rendering.
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Title: STMS: Smart Traffic Management & AI Object Tracking (PyQt6 & YOLOv8)
Description: Built a real-time computer vision desktop dashboard to run custom-trained YOLOv8 vehicle detection and tracking models.
Thread-Isolated GUI: Implemented PyQt6 QThread isolation to run real-time AI inference at 60fps without freezing the UI.
Model Optimization: Trained custom YOLOv8 detection models and compiled them via ONNX Runtime for optimized CPU/GPU execution.
Multi-Object Tracking: Integrated DeepSORT pipelines to automate vehicle logging, classification, and analytics.
Keywords: Python GUI, PyQt6, computer vision app, custom YOLOv8, object detection, ONNX Runtime, multi-camera tracking.
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Title: Death Realm (DR): Custom Unreal Engine C++ Subsystems
Description: Developed custom editor plugins and native performance utilities in C++ for the Unreal Engine 5 gameplay pipeline.
Editor Workflow Plugins: Built custom editor utilities using C++ and Slate UI to automate internal asset validation checks.
Telemetry & Tracking: Developed native performance-monitoring modules to trace memory allocations and prevent leaks in real-time.
Subsystem Optimization: Implemented optimized gameplay subsystems in C++ to bypass heavy blueprint runtime overhead.
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Title: HELIX: Native C++ Client Architecture & Telemetry
Description: Architected a high-performance native C++ standalone client utility to execute background automation tasks and collect system telemetry.
Client Architecture: Engineered a lightweight compiled C++ binary running asynchronous tasks.
Low-Level Systems: Utilized Win32 system APIs for local telemetry collection with zero main-thread overhead.
Memory Optimization: Implemented strict memory management routines keeping runtime overhead under 15MB.
Keywords: C++, client architecture, systems programming, native utility, telemetry client, memory optimization.
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