Ryan Jeon||
I am a fifth-year Ph.D. candidate in Data Science Department at Bowling Green State University, advised by Prof. Shuteng Niu.
My research advances AI by integrating Knowledge Graphs (KG) with Large Language Models (LLM), focusing on accuracy and robustness. I address LLM βhallucinationsβ through domain-specific fine-tuning and Retrieval-Augmented Generation (RAG). Additionally, I enhance graph-based models with continual learning techniques and develop defenses against adversarial attacks. By blending KGs with LLMs, I aim to improve context awareness in recommendation systems and reliability in question-answering platforms.
Prior to joining BGSU, I received my MS in Technology Management from Gies College of Business at University of Illinois at Urbana-Champaign. During that time, I managed multiple strategic business projects as a project manager.
Latest News
- Aug. 2024π¨π»βπ» Panelist @ Graduate Student Organization
- Mar. 2024π¨π»βπ» Paper Reviewer @ KDD 2024
- Jan. 2024πΒ Paper Presentation @ ISIITA 2024
- Oct. 2023π¨π»βπ» Panelist @ Student Perspectives on AI
- Nov. 2022πΒ Paper Presentation @ IPCCC 2022
Publications and Papers Under Review
- Flexible Memory Rotation (FMR): Rotated Representation with Dynamic Regularization to Overcome Catastrophic Forgetting in Continual Knowledge Graph LearningAnonymousSubmitted, 2024
- KGIF: Advancing Graph Attention Networks for Relation aware recommendations through Information FusionAnonymousSubmitted, 2024
- Reinforced Contrastive Graph Neural Networks (RCGNN) for Anomaly DetectionZenan Sun, Jingyi Su, Dong Hyun Jeon, Alvaro Velasquez, Houbing Song and Shuteng NiuIEEE IPCCC, 2022