Abdulghani Altaweel

- Developed and integrated embedded AI solutions for industrial applications - Trained and optimized ML models; built training and annotation pipelines - Applied quantization speed up on-device inference - Built C++/Python inference software (standalone and integrated) - Deployed ML from PoC to series production on NVIDIA, TI, and Intel - Real-time inference: ~190 FPS on TI AM68x (TDA4x), ~160 FPS on Jetson Orin NX - Collaborated with hardware and systems teams

- Embedded Linux: built and maintained the root filesystem with Yocto (custom layers and recipes) - Configured and adapted the Linux kernel and U-Boot bootloader - Automated release management of new OS images via CI/CD pipelines - C++ development for industrial camera systems (machine vision) - Error analysis and debugging of embedded software on target hardware

- Developed MATLAB software for measurement-data analysis - Analyzed data to detect and diagnose errors - Supported the installation of a new sensor system

- Master Thesis: "Development and validation of a deep-learning approach for determining the robustness of grasp points for robot-based grasping" - Research project: "Comparison of different CDCs and MCUs for Capacitance Measurement" - Specialization Modules: Microsystems and Control Engineering - Grade: Good

Bachelor Thesis: Navigation Mobile Robot Grade: Good