History
GyeongNam Science High School (Mar. 2019 ~ Feb. 2021)
High School Diploma - Early Graduation.
Korea Advanced Institute of Science and Technology (Mar. 2021 ~ )
Candidate for Bachelor of Science in Electrical Engineering and Computer Science.
Key Coursework
Circuits & EE
EE201 Circuit Theory
EE202 Signals and Systems
EE210 Probability and Introductory Random Processes
EE211 Introduction of Physical Electronics
EE303 Digital System Design
EE304 Electronic Circuits
EE305 Introduction of Electronics Design Lab.
EE362 Semiconductor Devices
EE403 Analog Electronic Circuits
EE432 Digital Signal Processing
EE571 Advanced Electronic Circuits
Programming & Systems
EE209 Programming Structures for Electrical Engineering
CS220 Programming Principles
CS230 System Programming
CS311 Computer Organization
CS320 Programming Language
CS330 Operating System and Lab
CS341 Introduction to Computer Networks
CS Theory & AI
CS204 Discrete Mathematics
CS206 Data Structure
CS300 Introduction of Algorithms
CS306 Introduction to Database
CS376 Machine Learning
Republic of Korea Army (Jan. 2024 ~ July. 2025)
Sergeant - Honorably discharged upon completion of mandatory military service.
Research Experience
Runtime-Adjustable Approximate Multiplier Research
KAIST, EPIC Lab. | Prof. Lee, Youngjoo | 2026.03 ~ Present
- Investigated the architectures of exact multipliers, implementing them at the Register-Transfer Level (RTL) to evaluate and compare their Power, Performance, and Area (PPA) metrics.
- Currently developing an advanced approximate multiplier architecture that dynamically adjusts the error rate at runtime, optimizing the trade-off between computation accuracy and hardware efficiency.
Analysis of DETR Model and Comparative Study of Backbone Performance
KAIST, Video and Image Computing Lab. | Prof. Kim, Mun-churl | 2025.06 ~ 2025.08
- Analyzed the core concepts and evolution of object detection by reviewing seminal papers including YOLO, Transformer, DETR, and Swin Transformer to understand their fundamental principles.
- Designed and executed a comparative experiment to address DETR's limitations, such as slow convergence, by establishing a deep learning server environment and replacing the standard ResNet-50 backbone with a Swin Transformer.
- Determined from initial loss analysis that the ResNet-50 backbone demonstrated superior performance in training speed, stability, and generalization, concluding that the Swin Transformer's local attention mechanism likely impairs the global context modeling fundamental to DETR.
8-bit 100MS/s full-binary Current Steering DAC
KAIST, Mixed Signal Integrated Circuits Lab. | Prof. Ryu, Seung-Tak | 2023.06 ~ 2023.08
- Investigated basic D/A Converter and Sampling Theory, focusing on the factors that increase the nonlinearity of Current-Steering DAC and studied how to reduce this effect in the circuit.
- Designed Current Cell and Switch Driver on TSMC-180nm in OrCAD, and validated performance through testbench simulation (60dB SFDR at Nyquist frequency).
- Improved performance by changing CMOS conditions for 2Gs/s clock frequency operation (58.3dB SFDR at Nyquist frequency).