PHAn Hoàng

Over 2 years of experience in C/C++ programming for software and embedded system development. Experienced in developing AI camera / computer vision related projects. Proficient in working with Windows and Linux operating systems.

Experienced in developing internal tools for debugging, testing, and workflow optimization. Skilled in debugging, performance optimization, and troubleshooting at system/application level. Strong analytical thinking, proactive learning attitude, and effective teamwork skills

Developer at Wisenet Open Application (2025-04 – 2026-03)

Ported and optimized all core features from the Zeppelin platform (Ambarella CV2) to the Wisenet Open platform running on CV5-WN9 chipset, ensuring compatibility, performance stability, and scalability for next-generation AI camera systems.

• Conducted in-depth analysis of the Wisenet Open platform architecture, including SDK, middleware, and system constraints.
• Collaborated directly with customers and onsite PMs to gather requirements, analyze issues, and propose technical solutions aligned with product goals.
• Ported and integrated core features from legacy platform to new architecture, ensuring backward compatibility and system stability.
• Integrated communication protocols and AI libraries into camera firmware, enabling advanced video analytics capabilities.
• Optimized system performance by monitoring and tuning CPU and memory usage on embedded devices.
• Deployed AI powered application on prototype hardware, performing functional and performance testing.
• Performed code reviews, enforced coding standards, and improved code quality and maintainability.
• Worked closely with cross-functional teams (QA, hardware, AI) to ensure seamless integration and delivery.

Developer at MCC Project (2024-10 – 2025-03)

Developed an MCC system for an Arab customer to detect traffic-related objects and events (traffic jam detection, pedestrian detection, wrong-way vehicle detection, commercial vehicle detection, etc.) from vehicles on city roads, and transmit detection results to the customer's server.

• Analyze requirements and API specifications provided by the customer.
• Develop UI to monitor and set server configuration, camera configuration
• Design and implement a local database using SQLite to store authentication and event data, ensuring data backup when the system cannot connect to the server.
• Implement token-based authentication, including access token retrieval and refresh mechanism.
• Read AI detection results from the camera and send data to the customer's server using CURL and HTTP APIs.

Developer at Camera WiseAI application (2024-01 – 2024-09)

Develop new features for AI-powered camera applications.

• Develop backend for WiseAI camera features including Detection Feature (Object Detection, IVA, Line Crossing, Stopped Vehicle Detection, Pedestrian Detection) and statistics feature (object counting - vehicle queue management – vehicle heatmap report), etc…
• Integrate with Protocol team to handle configuration IPC from WebViewer.
• Handle WNVA library detection result to output log to Webview through Protocol shared memory
• Test and integrate application with Protocol API using PostMan
• Debug issue and test application event and metadata using ONVIF Device Manager and SUN API tools

Mechatronics Engineering – University of Transport and Communications