About Me
Hi, my name is Kyungbin (binbin), and I am a Master’s student in Electrical & Electronic Engineering at Korea University (Advisor: Professor Yunho Oh).
My research focuses on next-generation memory systems, specifically Compute Express Link (CXL) and tiered memory management for AI and high-performance computing (HPC).
I have experience in low-level system programming, memory optimization, and performance tuning for large-scale computing environments.
Previously, I analyzed LLM inference performance on tiered memory systems, evaluating memory access patterns and system efficiency.
My work involves developing advanced memory management techniques, optimizing data locality, and reducing access overhead in AI workloads.
I specialize in: Memory Systems, Operating Systems, and Low-Level System Programming.
Research
Memory Systems
Exploring next-generation memory architectures to enhance performance and scalability in AI and high-performance computing.
My research focuses on advanced memory architectures to support the evolving demands of modern computing.
I explore CXL-based memory disaggregation and tiered memory systems to improve resource utilization and system performance.
- Investigating CXL-enabled memory pooling to enhance datacenter scalability.
- Optimizing tiered memory management for AI and high-performance computing (HPC).
- Implementing hotness-aware memory techniques to improve data locality and reduce access latency.
- Developing memory optimization strategies to enhance efficiency in large-scale computing environments.
This research aims to advance memory-centric computing, ensuring efficient and scalable memory solutions for AI, cloud computing, and HPC.
Experience
Optimized microLED transfer processes through data-driven analysis and defect reduction strategies.
Led the development and optimization of microLED transfer processes in collaboration with Apple, ensuring high yield and scalability.
- Collaborated with Apple to refine MTT (MicroLED Transfer Technology) specifications and improve AOI accuracy.
- Automated wafer defect analysis using macros & VBA, improving defect detection efficiency.
- Developed XML conversion tools to streamline defect data processing.
- Analyzed OEE (Overall Equipment Effectiveness) to optimize production capacity and equipment requirements.
- Designed and conducted reliability tests, including Fiducial Quality verification, Nano Bump analysis, and Clamp Time Sweep.
- Implemented Adaptive Maintenance strategies to enhance production stability.
Education
Korea University
MS in Electric & Electronic Engineering
Setpember 2024 - Present
Advancing expertise in system software and high-performance computing,
focusing on machine learning performance optimization and memory management.
Researching CXL technology and low-level system programming, leveraging C, C++, and Python.
Dongguk University
BS in Electronic & Electrical Engineering
March 2016 - February 2022
Studied object-oriented programming (C++) and computer algorithms, developing strong analytical skills.
Completed external training in digital system design, gaining experience with HDL and FPGA programming.
Led a senior capstone project, designing a smart advertisement cart using E-paper, ESP32, and Bluetooth for real-time ad updates.
Designed and prototyped custom PCB circuits, optimizing power management and signal integrity.
Skills
Language
- Korean: Native
- English: Professional
Programming Languages
- C, C++
- Python
- Shell Script