CV

Ph.D. in Statistics and Data Science

• Advisor: Jy-yong Sohn
• GPA: 4.14 / 4.3

B.S. in Applied Statistics and Data Science

• GPA: 3.83 / 4.3

Research Intern

Research Intern

• Developed a text embedding model using Mistral 7B
• Conducted experiments on MTEB benchmark dataset
• Contributed to a technical report

Research Intern (Vocational Training Program)

• Implemented Neurocard, a data-driven cost estimation model for query optimization
• Built APIs to be incorporated in the database system

Ph.D. Student

• Developed APIs supporting RAG and Multi-Agent Debate system
• Conducted experiments on the AGIEval benchmark, achieving performance comparable to GPT-4 on the LSAT domain

Undergraduate Researcher

• Researched data importance-aware scheduling to exploit diversity in distributed data settings
• Designed and evaluated scheduling algorithms

Teaching Assistant — Introduction to Information Theory for Data Science

Teaching Assistant — Introduction to Optimization for Data Science

Academic Affairs Chair, Data Science Lab (Undergraduate Academic Society)

• Supervised Learning
• BERT & Generative Models
• Seq2Seq Implementation

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective

• Joonkyu Kim, Yejin Kim, Jy-yong Sohn

Aligning large language models for cognitive behavioral therapy: a proof-of-concept study

• Yejin Kim, Chi-Hyun Choi, Selin Cho, Jy-yong Sohn, Byung-Hoon Kim

ERD: A Framework for Improving LLM Reasoning for Cognitive Distortion Classification

• Sehee Lim, Yejin Kim, Chi-Hyun Choi, Jy-yong Sohn, Byung-Hoon Kim

ERD: A Framework for Improving LLM Reasoning for Cognitive Distortion Classification

Object Detection on Satellite Imagery

Neural Radiance Fields (NeRF)

Text Style Transfer

Embedding-based Recommendation (MaskRCNN)

Eye-Tracking Data Analysis (Tobii I-VT Filter)

GPT Prompt for Domain-Specific Tasks

Data-driven Query Optimization (Neurocard)

Federated Learning