Machine Learning Researcher · NAVER
Jin-Duk Park
I work on NAVER's Shopping Search Ranking Team. My experience includes search ranking models for billions of products, agentic workflows and batch processing, and knowledge graphs.
I received my Ph.D. in Computational Science and Engineering from Yonsei University, where I studied graph learning and recommender systems.

News
Our work on scalable collaborative filtering was accepted to IEEE TKDE.
I received my Ph.D. from Yonsei University.
Our work on graph alignment was accepted to IEEE TNSE.
I joined NAVER as a Shopping ML Researcher.
Two papers on recommender systems were accepted to WWW 2025—one as first author and one as corresponding author.
Earlier updates · 2020—2024
I was selected as a Ph.D. research scholarship recipient by Samsung Electronics.
I gave an invited talk on LLMs and mixture-of-experts models at NAVER Cloud (CLOVA).
Two papers on recommender systems were accepted to SIGIR 2024.
I began a research internship at NAVER Cloud (CLOVA).
I gave an invited talk at the third Graph User Group seminar in Korea.
I received a Best Paper Award from KICS.
I presented our work in the Recommendation with Graph session at KDD 2023 in Long Beach, California.
I gave an invited talk at Prof. J. C. Moon's group at California State University, Long Beach.
Our work on graph alignment was accepted to IEEE TPAMI.
Our work on recommender systems was accepted to KDD 2023.
I spoke at a joint meeting with Monash University, UNSW, and CUHK.
I gave an invited talk at Prof. Xin Cao's group in the UNSW School of Computer Science and Engineering.
I conducted a visiting research program with Prof. Xin Cao's team at UNSW, Australia.
I presented at the Tokyo A3 Workshop in Japan.
I received the Best ML Paper Award at the first Yonsei AI Workshop.
Our work on network alignment was accepted to AAAI 2022 and CIKM 2022.
I attended KDD 2022 in Washington, D.C.
I received the KICS President's Outstanding Paper Award.
I received the Outstanding Poster Award from Yonsei University's Department of Computer Science and Engineering.
Our work on explainable AI was accepted to PLOS ONE.
Our work on smart-manufacturing anomaly detection was accepted to IEEE Access.
I began a collaboration with Prof. J. C. Moon's group at CSULB.
Experience & education
- 2025—Present
NAVER
Machine Learning Researcher · Shopping Search Ranking Team
Search and recommendation in the shopping domain.
- 2020—2025
Yonsei University
Ph.D., Computational Science and Engineering
Graph learning, graph mining, recommender systems, and network alignment. B.S. in Mechanical Engineering, 2012—2018.
- 2024—2025
Samsung Electronics
Research Scholar · Language AI Team
Selected for the Samsung Electronics research scholarship program.
- 2024
NAVER Cloud (CLOVA)
Research Intern
LLMs, vision-language models, video-language models, fine-tuning, and language data collection and generation.
- Jan.—Mar. 2023
University of New South Wales
Visiting Researcher · BK21 Overseas Study Program
Recommender systems research advised by Prof. Xin Cao.
- 2020—2021
California State University, Long Beach
Visiting Researcher · Remote
Explainable AI research advised by Prof. J. C. Moon.
- 2017—2019
LG Electronics
Software Researcher & Project Manager
Intern in 2017; full-time researcher from 2018 to 2019 at LG Digital Park.