About Me
Who I Am
Hello! I'm Xinyuan Tong, a Computer Science student driven by the vision of democratizing artificial general intelligence (AGI). My ultimate aspiration is to design systems that make cutting-edge AI accessible, efficient, and sustainable for all. Currently, I'm an exchange student at the University of Southern California, while pursuing my Bachelor's degree at the University of Edinburgh.
I'm passionate about tackling complex problems at the intersection of distributed systems and AI, constantly striving to improve my skills through challenging projects. My interests span across multiple domains within Computer Science, with a particular focus on scalable AI systems, machine learning infrastructure, and computational efficiency.
In addition to my technical pursuits, I value collaboration and knowledge sharing as essential elements in advancing AI accessibility. I've served as a Teaching Assistant, helping other students grasp complex concepts in computer science and fostering a community of future AI innovators.
Education
University of Southern California
Los Angeles, CA, USA
Bachelor of Science in Computer Science (Exchange Student)
August 2024 - May 2025
University of Edinburgh
Edinburgh, UK
Bachelor of Science in Computer Science
September 2022 - June 2026
GPA: 3.9/4.0
Highlighted Courses
Algorithms and Data Structures
Computer Systems
Data Science
Software Engineering
Experience
Undergraduate Research Assistant
University of Edinburgh
June 2024 - Present
- Collected and preprocessed over 100 research data samples from online sources, including data cleaning and classification using Python
- Annotated more than 20 data samples and utilized AI tools to establish a standardized data annotation workflow, enhancing efficiency by 30%
Teaching Assistant
University of Edinburgh
September 2023 - December 2023
- Guided over 50 students, simplified complex concepts for enhanced comprehension
- Adapted teaching strategies based on student feedback, improving the clarity and effectiveness of instruction
- Contributed to students' ability to understand and apply computation principles effectively, as evidenced by positive feedback and improved course performance metrics