Projects
Sung Oh's personal projects.
VT Copilot
An intelligent assistant designed to help students make informed course decisions. It features interactive data visualizations generated by a data analyst agent, which scrapes publicly available information from the web and transforms it into interactive graphs. Built with Next.js, FastAPI, and SQLite.
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Explore Public's Perspectives on Generative AI in Computer Science (CS) Education: A Social Media Data Analysis
This project involved analyzing public sentiment towards Generative AI in CS education using both BERT-based models and Large Language Models (LLMs). I collected and filtered Reddit comments to identify key concerns and benefits of Generative AI tools in educational settings. The findings reveal a general positive sentiment towards the use of AI for learning but also highlight challenges such as academic dishonesty and over-reliance on AI.
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Fintellection
I created the Fintellection, an AI-powered search engine that fetches and displays real-time financial data from the internet. Utilizing advanced techniques such as Retrieval-Augmented Generation (RAG), embeddings, and similarity searching, it delivers accurate and insightful financial information promptly.
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Smart Workout Tracking Solution for Outdoor Fitness
I developed a user-centered smart workout tracking system for outdoor fitness. It leverages mobile and smartwatch technologies to provide real-time data and personalized exercise plans, enhancing the outdoor workout experience.
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Solar Powered Autonomous Drone
I created a project to develop solar-powered autonomous drones, addressing sustainability concerns associated with current battery-operated drones. By integrating solar panels, these drones reduced reliance on non-renewable energy sources, promoting a more environmentally friendly and efficient solution for drone technology.
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Google Datacenter Workload Characterization
I worked on the Google Datacenter Workload Characterization project, which involved analyzing and visualizing data from Google's production systems using Matlab. The project focused on understanding task and job patterns, resource usage, and identifying correlations between CPU and memory consumption within the dataset.
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