About

Sung Oh is an undergraduate Computer Science student at Virginia Tech, maintaining a 3.89 GPA while conducting cutting-edge research across two laboratories. At the Tech on the Trail Lab, he fine-tunes and applies large language models to enhance computer science education platforms. Concurrently, his work at the IDEEAS Lab focuses on applying natural language processing techniques to analyze social media sentiment toward generative AI in CS education. His research contributions have resulted in first-author publications at venues including IEEE FIE and ACM CHI, demonstrating his ability to produce impactful academic work as an undergraduate.

Sung's industry experience includes a software engineering internship at Fasoo, where he developed a real-time speech-to-text system using WebSockets and Voice Activity Detection (VAD), achieving significant improvements in both transcription speed and accuracy. He is proficient in Java, Python, TypeScript, and various machine learning frameworks. Currently, he serves as a Research Assistant at Abear, where he builds sophisticated content generation pipelines leveraging multiple vision models, further expanding his expertise in AI-driven applications.