About me
I am a Ph.D. student in Electrical and Computer Engineering at Purdue University, with a strong commitment to advancing machine learning through both rigorous research and practical application. My primary research focus lies in trustworthy AI, particularly in debiasing multimodal systems. I explore post-hoc approaches that mitigate fairness issues in large vision-and-language models, aiming to ensure equitable performance across demographic groups without the need for retraining. I am also interested in machine learning under limited data settings, including positive-unlabeled learning and novel category discovery, to enable robust learning in data-scarce environments.
In addition to my academic research, I pursue industrial applications of machine learning, such as developing generative models for inverse problems in antenna design and building datasets and foundational models for industrial sound AI. These efforts reflect my broader goal of connecting methodological advancements with practical impact across diverse engineering domains.
News
- May 2025 – I began my summer internship as a Research Scientist at Samsung Research America!
- January 2025 – My paper ALFA was accepted to ICLR 2025!
- October 2024 – My work NCD-DLT was accepted to WACV 2025!
- October 2024 – I received the NeurIPS 2024 Scholar Award!
- October 2024 – My paper FOPU was accepted to the EMNLP 2024 Industry Track!
- October 2024 – My BE-Module paper surpassed 100 citations!
- September 2024 – My paper SFID was accepted as a Spotlight at NeurIPS 2024!
- May 2024 – My paper on explainable antenna design was accepted to IEEE APS 2024!
- January 2023 – I began my Ph.D. program at Purdue University.
- August 2022 – I completed my Master’s degree at Seoul National University.
- September 2021 – My paper BE-Module for satellite image segmentation was accepted to IEEE TGRS.
- September 2020 – I started my Master’s program at Seoul National University.