JeongHyeon Kim

Hello! My name is Jeonghyeon Kim, and I am a Ph.D. student in Data Science at SeoulTech, advised by Prof. Sangheum Hwang of DAINTLAB.

🧗‍♂️I am dedicated to enhancing the reliability and interpretability of AI systems, particularly through:

• Out-of-distribution detection (OoDD)
• LLM unlearning
• Energy based models (EBMs)

⭐️Research Focus

My research explores OoDD in vision-language models (VLMs) like CLIP, leveraging multi-modal fine-tuning (MMFT). In our work, we have addressed the modality gap between image and text embeddings through cross-modal alignment (CMA), enhancing the utilization of pretrained knowledge. Moving forward, we aim to extend this research to multi-modal pre-training and integrate large language models.

I am also interested in LLM unlearning, with a particular focus on preserving utility performance while effectively unlearning target knowledge. I have developing strategies for dataset sampling methods that optimize the balance between forgetting targeted information and maintaining model utility.

💥Ultimate Goal

To develop AI systems that are reliable, and interpretable, ensuring their trustworthy deployment in real-world applications.