Ms. Yuri Kim, Korea University, South Korea
Yuri Kim is a Ph.D. candidate in Computer Science at Korea University, Seoul, South Korea, where she has been conducting research since September 2020 as a recipient of the ICT Elite Talent Development Program Scholarship. She holds a B.Sc. and M.Sc. in Computer Science from Eötvös Loránd University, Budapest, Hungary, where she graduated with distinction under the Stipendium Hungaricum Scholarship. Yuri has extensive experience in both academia and industry, having served as a lecturer at Korea University Graduate School of Education and Eötvös Loránd University, teaching advanced data structures and functional programming. She has also worked as a project manager at The Mihalik Group, leading the development of in-house business automation software, and as a student backend developer at Ericsson. Her research interests span natural language processing, machine learning, and financial modeling, with notable publications on stock trading recommendation systems, serendipity-based recommender systems, and Linked Open Data structures. She has been actively involved in entrepreneurial ventures, participating in the 2024 Korean I-Corps Program and the 2023 Innovation Startup School, focusing on AI-driven solutions. Proficient in Python, C, Go, and Clean, Yuri combines her expertise in programming with strong project management skills in Agile and Scrum methodologies.
Professional Profile:
ORCID
Summary of Suitability for the Best Researcher Award
Yuri Kim is an exceptional researcher in computer science, artificial intelligence, natural language processing (NLP), and recommender systems, demonstrating a strong academic and professional background. Her diverse expertise, high-impact research contributions, and interdisciplinary approach make her a highly suitable candidate for the Best Researcher Award.
🎓 Education
📍 Korea University, Seoul, South Korea
🔹 Ph.D. Candidate in Computer Science (2020.09 – Present)
🔹 🎖️ Recipient of ICT Elite Talent Development Program Scholarship
🔹 🏫 Research Assistant
📍 Eötvös Loránd University, Budapest, Hungary
🔹 B.Sc. & M.Sc. in Computer Science (Integrated Program) (2016.09 – 2019.08)
🔹 📊 GPA: 4.28 / 4.5 (Master’s) | 4.48 / 4.5 (Bachelor’s)
🔹 🎖️ Recipient of Stipendium Hungaricum (Hungarian Government Scholarship)
💼 Work Experience
📍 The Mihalik Group, Chicago, IL (Remote)
🔹 Project Manager (PM) (2023.08 – 2024.07)
🔹 🏗️ Developed in-house business automation software
🔹 📅 Planned & designed project phases, coordinated schedules
🔹 🔍 Managed resources & monitored project performance
📍 Korea University Graduate School of Education, Seoul, South Korea
🔹 Lecturer – Advanced Data Structures (2022.09 – 2023.02)
🔹 🖥️ Delivered lectures on Data Structures & Algorithms
🔹 📝 Designed quizzes, assignments, exams & projects
🔹 📚 Developed instructional materials
📍 Eötvös Loránd University, Budapest, Hungary
🔹 Lecturer – Functional Programming (Clean Language) (2018.02 – 2019.02)
🔹 🏛️ Taught Clean Functional Programming
🔹 ✍️ Designed evaluations, assignments, exams & projects
🔹 📖 Created instructional materials
📍 Ericsson, Budapest, Hungary
🔹 Student Backend Developer (2018.09 – 2019.01)
🔹 ⚙️ Developed & evaluated performance test cases using C
🔹 🛠️ Updated codebase to align with modern standards
🔹 🔍 Conducted code reviews & refactoring
🏆 Awards & Honors
🔹 2024 Korean I-Corps Program 🚀
- AI-Based Personalized Makeup Consulting
🔹 2023 Innovation Startup School 🏅
- AI-Based Celebrity Memorabilia Donation & Auction Platform
🎖️ Achievements
📌 Publications & Research 📚
🔹 Developed a Rule-Based Stock Trading Recommendation System 📈
🔹 Designed a Serendipity-Incorporated Recommender System 🤖
🔹 Implemented a Linked Data Visualization System 🔗
🔹 Proposed methods for Enhancing Linked Open Data (LOD) 🛠️
🔹 Researched Interdisciplinary Applications for Functional Programming 🎨
🔹 Compared Clean vs. C Programming for Education 💻
🔹 Explored Distributed Computation Patterns in Go & RabbitMQ ☁️
📌 Projects 🔍
🔹 SEC 13D/G & 13F Report Tracking Platform (2024.12) 📊
🔹 Text-to-Speech-Based Audiobook Auto-Generation (2024.12) 🎙️
🔹 AI Avatar-Based Motion Slide Auto-Generation (2024.12) 🖼️
🔹 DART Stock Large Shareholder Report Crawling System (2024.10) 📑
Publication Top Notes:
A Rule-Based Stock Trading Recommendation System Using Sentiment Analysis and Technical Indicators
Introduction to programming Using Clean