- Explainable Artificial Intelligence
- Recommender System
- Received the B.A. Degree in Business Administration from Sungkyunkwan Univ., Seoul, Korea (Mar., 2012 ~ Feb., 2018)
- Received the M.S. Degree in Statistics from Sungkyunkwan Univ., Seoul, Korea (Mar., 2018 ~ Aug., 2020)
- Researching at the Data Intelligence Lab. as a Ph.D. Candidate in Artificial Intelligence from Hanyang Univ., Seoul, Korea (Mar., 2021 ~)
- [Doosan Bobcat] ๋ง์ผ ๋ฐ์ดํฐ ๊ธฐ๋ฐ ์์ต ๊ทน๋ํ๋ฅผ ์ํ ๊ฐ๊ฒฉ ์์ฌ๊ฒฐ์ ์ค๋ช ๊ฐ๋ฅํ A.I. ๋ชจ๋ธ ์ฐ๊ตฌ (Jun., 2022 ~ May, 2023)
- [Samsung Electronics] ๋ฐ๋์ฒด ๊ณต์ ๊ฒฐํจ ์์ธก ๋ฐ ์์ง ์ ๋น๋ฅผ ์ํ ์ค๋ช ๊ฐ๋ฅํ A.I. ๋ชจ๋ธ ์ฐ๊ตฌ (Mar., 2023 ~ Feb., 2025)
- [Hyundai Motor] ์ฐจ๋ ๋ถํ ๊ณ ์ฅ ์ง๋จ ๋ฐ ์์ง๋ฅผ ์ํ ์ค๋ช ๊ฐ๋ฅํ A.I. ๊ธฐ์ ๊ฐ๋ฐ (Mar., 2024 ~ Nov., 2024)
- ํฉ์ฑํ, ์ฑ๋๊ท, ์ด์์ฒ , ํ์ ํํฐ๋ง์ ์ ํ๋ ํฅ์์ ์ํ ๋จ๊ณ์ ์ฆ๋ถ ๊ธฐ๋ฐ์ ๋ฐ์ดํฐ ์ํจํ ์ด์ ๊ธฐ๋ฒ, in KSC 2021, Dec. 20-22, 2021
- ์ ํฌ์ค, ํฉ์ฑํ, ์ฑ๋๊ท, ํ๋ฃจ๋ ๊ธฐ๋ฐ์ ํฌ์ ํ๋ จ์ ํ์ฉํ ํ์ ํํฐ๋ง ๋ชจ๋ธ ๊ท์ ๋ฐฉ์, in KSC 2023, Dec. 20-22, 2023
- Sunghyun Hwang and Dong-Kyu Chae, An Uncertainty-Aware Imputation Framework for Alleviating the Sparsity Problem in Collaborative Filtering, in CIKM 2022, Oct. 17-21, 2022 (A/R: 23%)
- Sunghyun Hwang, Sangmyeong Lee, Eunjung Choi, Jongsoo Lee, and Dong-Kyu Chae, An XAI Model for Semiconductor Manufacturing Processes with Exploring Process Parameter Interactions based on Uncertainty, in KISM 2023, Nov. 19-23, 2023
- Sangmyeong Lee, Sunghyun Hwang, Eunjung Choi, Xueyi Zhou, and Dong-Kyu Chae, An XAI Model for Semiconductor Manufacturing Processes based on Confidence Interval Visualization for the Impact of Process Parameters, in KISM 2023, Nov. 19-23, 2023
- Yoo Hyun Jeong, Sunghyun Hwang and Dong-Kyu Chae, HiLite: Hierarchical Level-implemented Architecture Attaining Part-Whole Interpretability, in CIKM 2024, Oct. 21-25, 2024 (A/R: 23%)
- [SIGIR Student Travel Grants] An Uncertainty-Aware Imputation Framework for Alleviating the Sparsity Problem in Collaborative Filtering (Oct. 17-21, 2022)
- [Ph.D. Fellowship from NRF of Korea] Research on Enhancing Explainability of AI via Uncertainty Quantification (Sep., 2024 ~ Aug., 2025)