Omar Alsabbagh

ad0pg2@r.postjobfree.com 916-***-**** Linkedin.com/in/omaralsabbagh17

EDUCATION:

University of California-Davis Graduated: September 2023 Bachelor of Science in Computer Science Minor in Electrical Engineering GPA: 3.3 / 4.0 SKILLS:

• Embedded systems: Advanced proficiency in C/C++, ARM Cortex-M based MCUs, and writing embedded code both in register level and HAL level. Proficient in RTOS, Embedded Linux.

• Assembly Language: Experience in both ARM, and RISC-V assembly.

• OS programming: Process management, Memory management, File Systems

• Other: STM32 CubeIDE and CubeMX, Python, Java, MATLAB, Pytorch, TensorFlow, Numpy, Pandas EXPERIENCE:

Embedded Systems Projects: July 2021 – Present

1. Real-Time Clock display

• Utilized Embedded C Programming on STM32F411 microcontroller to display real time and date on an LCD.

• Coded STM32F411 to configure and read data from DS1307 RTC via I2C interface. Then Transmitted data to LCD using UART protocol for user visibility.

• Developed device drivers for DS1307 and LCD display, enabling seamless interaction with the microcontroller. 2. Handheld Space invaders game

• Utilized Embedded C Programming on TM4C123GH6PM microcontroller to implement Space invader game.

• Using ADC to capture Slide Pot inputs which acts as Joystick. The game is displayed on Nokia 5110 display.

• Utilized DAC for Sound output. User engage with the game by pressing buttons that are connected to GPIO pins. Additionally, LEDs in MCU are programmed to enhance interactivity within the game. General Software Engineering Projects: January 2021 – Present 1. Operating System Programming

• implemented a shell-like command line interpreter, with support for I/O redirection, pipelines, and directory stack using C Programming Language.

• Designed a user-level thread API that encompasses a task scheduler, preemption support, and semaphore handling. 2. Machine Learning and Computer Vision

• Competed in Lyft's Motion Prediction for Autonomous Vehicles challenge, leveraging PyTorch for model training and predictions, and Python for data processing and analysis.

• Participated in “Deepfake Detection Challenge”, utilizing PyTorch, NumPy, Pandas, and Matplotlib to develop innovative technologies for detecting manipulated media. 3. Interactive Card Game with GUI

• Blackjack card game with user interface.

• Support for both SinglePlayer mode against AI opponents and multiplayer mode for remote human-to- human competition. Players use separate devices in multiplayer, with real-time data sync utilizing ThingSpeak.

4. Android Game

• Developed an Android game using Java. The game involved arithmetic challenges, where players solve sums or differences of random numbers, selecting the correct answer from four options to earn points.