Curriculum Vitae

• Multithreaded GUI Application for Automated ONT Testing:
• Tools/Technologies: C++, GTKMM, Boost.Asio, SSH2, MSYS2, JSON (nlohmann), Bash, GPON, Raspberry Pi and Glade (GUI);
• Developed a C++ application on Windows (using MSYS2) with a GTKMM GUI and Boost.Asio for telnet communication to automate testing
• of Optical Network Terminals (ONTs) via an Optical Line Terminal (OLT) and Raspberry Pi clients;
• Followed MVC architecture and implemented State and Command Patterns to ensure a clean separation of concerns, improving code
• modularity and maintainability;
• Integrated Glade XML for UI design, enhancing flexibility in interface adjustments;
• Automated SSH-based execution of Bash scripts on Raspberry Pi clients to validate ONTs, performing multiple Tests (Traffic - iperf3,
• Provision, Firmware, LED, Optical Module, Ethernet, Ping, Network Services - DNS and DHCP, Dying Gasp, Firmware Upgrade, WebPortal
• and Bias Current);
• Implemented a multithreaded environment, allowing concurrent execution of test cases across different test slots, triggered via the GUI,
• ensuring efficient resource utilization;
• Designed a robust state machine to handle automated telnet sessions and testing procedures;
• Final customer: SFR.
• Tools: MSYS2, MinGW-w64, g++, CMake, lld, Visual Studio Code, Valgrind, Git;

• V&V model (Verification and Validation Software);
• Use CAPL programming (C style) to create and execute Test Cases for Automotive;
• Work with CANbus and CANoe technologies;
• Software Testing Qualifications;
• Other tools: JIRA, Confluence, GitLab and Git.
• Final Customer: Capgemini/Renault;

• Industrialization Projects:
• Implementing a software control system in LabVIEW for a conveyor belt. The system includes a data matrix reader, a NI 6525 interface, a
• SQL database and a User Interface. The goal of the system is to filter PCBA (Printed Circuit board Assembly)
• units that have been tested before the coating process from those that have not been tested;
• Software Control for machine (AOI) using Halcon, OpenCV and Boost libraries in C++;
• Designed machine for testing PCB/PCBA using LabVIEW and TestStand;
• Innovation Projects:
• Designed and implemented software systems for Digital Twins based on AI (for example YOLOv4) to measure the available areas in
• the logistic area;
• Integrating FFmpeg (written in C) into a C++ application to decompress video streams from an IP camera for AI processing;
• Collecting data/images in Python;
• Data aguantation in Python;
• Utilizing YOLOv4 in C++ for object detection tasks on custom datasets.

• Building Vision Systems and software for automotive industry: Bosch, Borgwarner and Autoliv;
• Software in LabVIEW to measure the Vibration Level from Motor to evaluate the quality it for Allied Motion (NI PXI 1073, NI PXI-4461 and
• Ethernet/IP protocol);
• Embedded Software in LabVIEW to a Press Machine (CompactRIO - FPGA&Real Time in Xilinx Zynq, NI 9401, NI 9201 and Profinet) for
• Bosch Hungary and database in SQL;
• EPLAN for electrical projects;

• Making the product inspection based Automated Optical Inspection using several methods, as such Subtraction Background, Color and
• Template Matching - LabVIEW programming;
• Implementation the Brenner’s method in C programming/LabVIEW for evaluation of the focus of video;
• Defining Test Plans (Flashing and Electrical Tests), Test Strategies according to the Requirements.

• Improvement of the laboratory equipment based on the problem solving techniques;
• Working in function of the KPI's (Key Performance Indicators);
• Doing functional tests of the water heaters following the Test Plans;
• Reporting of the experimental results to the project teams;
• Analyzing the experimental data using tools such as, Python: Matplotlib;

The main goal of this internship was to work as an embedded systems developer, using affordable microprocessor boards such as Arduino and Raspberry Pi to measure the performance and efficiency of industrial equipment for Wickens Engineering Ltd.

The monitored equipment included punching machines, CNC drills and robotic welders. This provided an innovative way to collect performance data from older equipment that could not produce data independently.

• Built optoelectronic assemblies using infrared proximity sensors, UV photodiodes, ultrasonic distance sensors and accelerometers.
• Implemented Wi-Fi communication for remote equipment monitoring.
• Programming languages: C, C++, Java and Python.
• Algorithms and methods: checksum validation and Fast Fourier Transform (FFT).
• Software and tools: AVRDUDE, NetBeans, CATIA and MATLAB.