I work as a Software Engineer at AEye, a cutting-edge LiDAR company based in Silicon Valley, where I own all software interfaces that enable interaction with LiDAR sensors. My role focuses on translating sensor capabilities into robust, intuitive software tools that support both internal development and external demonstrations.

I design, develop, and maintain a real-time visualization tool that allows interaction with the sensor and showcases LiDAR point cloud data during demos and customer engagements. This tool integrates both aesthetics and functionality, including 3D point cloud rendering, GUI development with Qt, high-performance C++ back-end implementation, and network communication with the sensor. Beyond visualization, I also take ownership of additional software components that sit between the sensor and end users, such as SDKs, customer-facing tools, and ROS drivers. My responsibilities include defining APIs, ensuring cross-platform compatibility, and maintaining software quality under the stringent requirements typical of automotive and industrial LiDAR systems.

I contributed to the development of AI systems that generate automatic sports productions. This encompassed not only the implementation of these systems but also their comprehensive testing and quality assessment. My main tasks involved real-time video processing, including both high-level features such as 3D geometry and actions detection, and low-level features such as camera calibration and image quality optimization (i.e. 3A).

For all these tasks I combined C++ (using Visual Studio and Qt), Python (PyCharm), Squish, and bash scripting. The entire development process followed the scrum methodology, and I utilized management tools such as Jira, Confluence, and Git.

I implemented computer vision techniques for ADAS, with a specific focus on maintaining and improving extrinsic camera and lidar calibration applications. This included working on the back-end algorithms and designing the GUI. The scope of these applications extended to both internal use (ground truth among different departments) and external use (meeting client requirements).

My primary programming tools were C++ for implementation (using Qt and Visual Studio), and Python for testing (Spyder), applying OpenCV in both cases. Additionally, I utilized management tools like Jira and Git, along with camera communication tools such as PCAN-View and GStreamer.

I managed and developed all the software tasks required by Hemophotonics’ technology, which focuses on non-invasive optical monitoring. My main focus was on the LUCA project (http://www.luca-project.eu), a European project led by the world-renowned ICFO.

I used C++ (Qt) to accomplish a wide range of tasks, including data analysis (fitting), communications (TCP/IP and serial), integration of submodules (synchronization algorithms), and GUI design. Additionally, I was involved in firmware tasks, utilizing Teensy.