- Location
- Toronto, Ontario, Canada
- Bio
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Hello! I'm Omar Afify, a Computer Engineering student at Queen's University with a passion for data science and programming. I'm proficient in Python, Java, C/C++, SQL, and VBA, and have experience with a variety of tools and platforms such as MS Office, MySQL, Git, AWS, Hadoop, Spark, Jupyter, Tableau, RStudio, Jira, Windows OS, Linux/UNIX, Cadence Allegro, LTspice, and Arduino.
I'm currently pursuing my Bachelor's Degree in Computer Engineering with a Professional Internship, maintaining a high GPA of 3.87/4.3. I've also completed a Certificate in Data Science from the University of Waterloo, where I developed my skills in visualizing and analyzing complex data using Python, R, and SQL.
My professional experience includes a 12-month internship at Advanced Micro Devices (AMD) as a High-Speed Electrical Compliance Engineer Intern. Here, I leveraged my debugging skills and root cause analysis to expedite issue resolution, managed multiple Project Test Plans, and developed Python scripts for test automation.
In addition to my academic and professional pursuits, I've been involved in several extracurricular projects. I've worked on a data science project analyzing automobile accident data in Calderdale, England, and developed a Python Neural Network to classify handwritten digits with over 96% accuracy as part of the Queen's Machine Intelligence Design Team. I also programmed an autonomous rover capable of line tracking, flag retrieval, and obstacle navigation for a Mechatronics & Robotics Project.
I'm excited to bring my technical skills, problem-solving abilities, and passion for data science to the Riipen Level UP program. I look forward to gaining valuable experience, expanding my professional network, and developing essential skills for my future career.
- Resume
- Resume_Omar_Afify.pdf
- Portals
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Vancouver, British Columbia, Canada
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Toronto, Ontario, Canada
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Skills
Socials
Achievements
Latest feedback
Recent projects
Work experience
High-Speed Electrical Compliance Engineer Intern
Advanced Micro Devices (AMD)
Toronto, Ontario, Canada
May 2023 - April 2024
β’ Leveraged exceptional debugging skills and adept root cause analysis to expedite issue resolution, effectively collaborating with cross-functional teams across AMD and utilizing Jira ticketing to drive solutions and enhance data logging processes
β’ Utilized advanced High-Speed Scopes and Logic Analyzers for precise measurements, adhering to latest I/O Specifications
β’ Managed and executed multiple Project Test Plans simultaneously, overseeing the entire process from end-to-end
β’ Python Test Automation: Developed scripts to shorten test time, increase program coverage, and avoid tedious tasks
o Audio Config GUI: developed script to toggle channel count, bit depth, and frequency reducing audio test time by 70%
β’ Conducted in-depth HDMI, DP, and USB PHY and Link Layer/Protocol Compliance Validation (Eye, HDCP, DSC, FEC, Audio)
β’ Hosted 6 events to enrich company culture by organizing and leading the Professional Development Intern Committee
Education
Certificate, Data Science
University of Waterloo
September 2023 - September 2024
Bachelor's Degree, Computer Engineering
Queen's University
September 2021 - Current
Personal projects
Automobile Casualty Severity in Calderdale, England (2014-2018)
October 2023 - December 2023
β’ Handled, cleaned, and analyzed complex automobile accident data using Python, Pandas, and Geopandas in Jupyter
β’ Performed a comprehensive data analysis with a focus on road conditions and geographical attributes, leading to the identification of significant correlations with casualty severity
β’ Key Finding β The project highlights the critical role of geographical attributes in determining accident frequency and established a strong correlation between the specifics of an accident (βWhoβ attributes) and the severity of casualties
Autonomous Line-Following Rover
January 2023 - April 2023
β’ Collaboratively programmed an autonomous rover capable of line tracking, flag retrieval, and obstacle navigation
β’ Integrated sensors in Arduino for real-time obstacle detection, enabling dynamic path adjustment during operation
β’ Led in-depth system testing, achieving 4th place in class competition based on the roverβs proficient track navigation