Computer Scientist with a Bachelor of Science in Computer Science from The University of Texas at Dallas with interests in artificial intelligence and machine learning. Focused on building reliable, intelligent software and user-facing tools.
Last updated April 2, 2026.
Computer Scientist with a Bachelor of Science in Computer Science from The University of Texas at Dallas with interests in artificial intelligence and machine learning. Focused on building reliable, intelligent software and user-facing tools.
Email: oscarruenescampos@gmail.com
Master of Science in Artificial Intelligence Online, The University of Texas at Austin (Austin, Texas)
Present
Selected Coursework: Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Ethics of AI
B.S. in Computer Science, The University of Texas at Dallas (Richardson, Texas)
Aug 2023 - Dec 2025
CS^2 (Computer Science Honors Program), AIS (Artificial Intelligence Society)
Certificate in Data Science, The University of Texas at Dallas (Richardson, Texas)
Jan 2024 - Present
Selected Coursework: Software Engineering, Data Structures and Algorithms, Discrete Mathematics II, Systems Programming in UNIX and Other Environments, Computer Architecture, Artificial Intelligence, Machine Learning, Introduction to Statistial Learning, Scientific Computing using Python
AI Contractor, Handshake
Evaluation of AI models production of videos and images across various axes and dimensions, entity/motion recognition in computer vision models, and improvement of AI generated code through code comparison, correctness validation, and prompt engineering to fit the adjusted solution.
Undergraduate Certificate in Data Science, The University of Texas at Dallas (December 2025)
Foundational C# with Microsoft, freeCodeCamp (Feb 2024)
Languages: Python, Java, C++, C#, JavaScript, HTML, CSS, MIPS
Frameworks/Tools: Flask, .NET, PyTorch, Git
VibeMap - AI Playlist Curator - Built a Spotify playlist clustering app with Spotify OAuth/Web API integration, Deezer preview audio retrieval, a Flask REST backend, and a vanilla JavaScript frontend.
Used PyTorch + Hugging Face CLAP embeddings, librosa audio preprocessing, and scikit-learn PCA/K-Means with silhouette scoring to group tracks and generate vibe-based playlists; deployed with a split Railway backend and Netlify frontend.
Personal Portfolio Website - Responsive site to showcase projects and background.
AIS, SHPE, CS^2 Honors Program