To the Admissions Committee

Arizona State University

MS in Robotics and Autonomous Systems(AI concentration)

Dear Admissions Committee,

My name is euidong Lee, and I am a NAND Solution Engineer at SK hynix. Although my day-to-day work primarily focuses on firmware-level optimizations for NAND solutions, I have long recognized the broader potential of integrating advanced software approaches including AI into NAND manufacturing. In an effort to address specific yield challenges, I organized a small in-house venture project team to apply for the HiGarage program—SK hynix’s unique initiative that provides seed support for innovative in-house ventures. This team brought together production engineers and robotics colleagues to explore AI-based defect detection methods.

Because we had limited in-house expertise in AI, I reached out to Seokhee, whom I knew from a coding club outside our company. From the outset, his willingness to devote evenings and weekends—despite holding a separate full-time engineering position elsewhere—greatly impressed me. We needed someone who could translate manufacturing constraints into actionable software logic, particularly for defect detection and automated handling, and he delivered precisely that.

During our collaboration, Seokhee proved adept at “speaking multiple languages,” so to speak. He absorbed input from my NAND production teammates, learned the nuances of what constitutes a “true” wafer defect, and mapped that knowledge onto an AI-driven detection system. He also conferred with our robotics group, which set up a hardware arm to physically manage wafer flow. While I am not deeply familiar with AI pipelines, I observed how he introduced practical concepts—such as real-time image checks and “defect probability” thresholds—in a way that everyone could follow. In one instance, he quickly diagnosed a data-transfer bottleneck and revised the pipeline to ensure continuous image processing without overwhelming us with unnecessary technical jargon, all the while enabling us to collaborate smoothly to solve the problem together.

A particularly important outcome was a tangible boost in 3D NAND wafer yield, which I understand to be roughly 1.5% above our baseline figures. While that may not sound dramatic outside of semiconductor circles, it translates to significant savings at scale. Even more noteworthy was Seokhee’s inquisitive approach: he often asked “why” certain parameters mattered to the production flow and “how” the AI model could be refined to accommodate changing conditions. This curiosity, combined with his problem-solving drive, unified distinct pieces—firmware needs, domain knowledge, and robotic handling—into a cohesive solution.

Based on my experience, I am confident that Seokhee will flourish in your MS in Robotics and Autonomous Systems(AI concentration program). He brings genuine enthusiasm for AI-driven advancements and possesses a knack for integrating insights from various sources. His skill set, combined with his resourceful and communicative nature, should allow him to thrive in the rigor of a graduate environment—something he has already demonstrated by juggling full-time responsibilities while contributing to this project.

Should you wish to discuss Seokhee’s performance or potential further, I would be happy to share additional observations. You can reach me at [email protected]. Thank you for your time and consideration.

Sincerely,

euidong Lee NAND Solution Engineer, SK hynix Email: [email protected] LinkedIn: https://buly.kr/Csing7K