About
I am a first-year Ph.D. student in Computer Science at Purdue University, advised by Prof. Vamsi Addanki.
My research focuses on ML Systems. My research background is in computer architecture and large-scale AI models. My research interest is in ML systems, with a current focus on Prefill-Decode (PD) disaggregation and inference scheduling. I am particularly interested in the efficient deployment of large-scale AI models in large-scale data centers, considering both software and hardware aspects.
Education
Purdue University
Ph.D. in Computer Science, 2026–Present
Advised by Prof. Vamsi Addanki
Seoul National University
M.S. in Electrical and Computer Engineering, 2022–2024
Advised by Prof. Hyuk-Jae Lee
KAIST
B.S. in Electrical Engineering, 2014–2021
Publications
VERIFIER-FREE TEST-TIME SAMPLING FOR VISION-LANGUAGE-ACTION MODELS
Suhyeok Jang, Dongyoung Kim, Changyeon Kim, Youngsuk Kim, Jinwoo Shin
arXiv, 2025
Link to PaperProactivePIM: Accelerating Weight-Sharing Embedding Layer With PIM for Scalable Recommendation System
Youngsuk Kim, Junghwan Lim, Hyuk-Jae Lee, Chae Eun Rhee
IEEE Access, 2025
Link to PaperIndustry Experience
RLWRLD
Research Intern
South Korea · Aug 2025 – Jan 2026
SK Telecom
Research Intern
South Korea · Mar 2019 – Jul 2019
Teaching Experience
Teaching Assistant
CS 422 Computer Networks, Fall 2026–Present
Currently assisting lectures and mentoring students.
Project Mentor
Graduation Project for Undergraduate Students, Spring & Fall 2023
Teaching Assistant
400.018 Creative Engineering Design, Fall 2022–2023
Honors & Awards
Best TA Award
Seoul National University, Mar 2023
Cum Laude
KAIST, Aug 2021
B.S. in Electrical Engineering