Research Projects

Current Projects (* indicates PI)

FLAME-ARK: Federated Learning Multimodal Foundation Models for Medical Institutes (Arp. 2025 - Dec. 2029)

• Funded by Korean Ministry of Health and Welfare

• This research project is for verifying federated learning solutions for establishing multimodal foundational models across multiple medical institutes.

*NRF 개인기초연구 중견연구 과제(Sep. 2024 - Aug. 2027)

• Funded by NRF

• This research project is for developing continual learning of multimodal generative models, including the following issues: i) Unravelling how catastrophic forgetting occurs in generative models, ii) Explaining the synergetic effects between different modalities, and iii) Developing effective continual learning algorithms for multimodal deep generative models.

Graduate School of AI in UNIST (Apr. 2020 - present) - [link]

• • • Funded by IITP

    • Participated as a core professor

5T Space UNIST(지역지능화 혁신인재 양성과제, Jan. 2023 - Dec. 2029)

• Funded by IITP

Past Projects(* indicates PI)

*ETRI 위탁과제(다계층 연합학습 시뮬레이션 및 기여도 측정 도구 제작, Jun. 2024 - Nov. 2023)

• Funded by ETRI

• This research project is to develop a robust and flexible simulation environment for hierarchical and asynchronous federated learning algorithms.

한국-미국(NSF) 국립과학재단 국제 공동 연구(Dec. 2021 - Nov. 2024)

• Funded by IITP

• This research project is for developing privacy-preserving video caching algorithms based on federated learning.

• Collaboration with USC (Prof. A. Molisch), Kyunghee Univ. (Prof. Minseok Choi), and Inha Univ. (Prof. Yeongjin Kim)

• Academic results: 1 paper for domain generalization in AAAI 2023, 1 paper for multi-domain meta-learning in AISTATS 2024, 2 paper for federated learning in WACV 2024, ICML 2024 1 paper for intelligent communication in WoWMoM 2024, and 1 workshop paper in AAAI'23 workshop.

*NRF 개인기초연구 우수신진연구 과제(Mar. 2021 - Feb. 2024)

• Funded by NRF (National Research Foundation)

• This research project is for developing context-aware self-growing continual meta-learning with a few training data samples.

• Academic results: 1 paper for generalization in AAAI 2023, 1 paper for few-shot class-incremental learning in WACV 2024, 1 paper for multi-domain meta-learning in AISTATS 2024.

*ETRI 위탁과제(다중 추론 성능 기반 연합학습 비동기 합의 실험 환경 구축, Jun. 2023 - Nov. 2023)

• Funded by ETRI

• This research project is for developing a hierarchical and asynchronous federated learning algorithm.

*ETRI 위탁과제(자원 은닉형 딥러닝 모델 실현 가능성 검증 기술 개발, Apr. 2023 - Nov. 2023)

• Funded by ETRI

• This research project is for developing double-blind federated learning algorithms that secure both models and data.

ITRC 대학 정보통신기술 연구센터(Jan. 2021 - Dec. 2022)

• Funded by IITP

• This research project is for developing machine learning algorithms for energy-efficient wireless sensor management.

• PI: Prof. Franklin Bien (UNIST EE)

Mobility-On-Demand AI Technologies for Autonomous Vehicles (Mar. 2021 - Feb. 2023)

• Funded by UNIST and (주) 씨엘

Multi-objective Neural Combinatorial Optimization Algorithm (Mar. 2021 - Feb 2023)

• Funded by UNIST and EpiSci

*LG H&A 산학 연구 과제(Jul. 2022 - Jan. 2023)

• Funded by LG 전자 H&A

*고효율/고신뢰 연소 시스템을 위한 실 데이터 기반 강화 학습 솔루션 개발 (Jan. 2022 - Dec. 2022)

• Funded by 삼양사(주) & UNIST

• This research project is for developing high-efficient and reliable combustion control systems based on deep reinforcement learning algorithms.

*Machine Learning for Error-Correcting Codes (May 2020 - Nov. 2020)*

• • • Funded by, ETRI

    • Our research part is focused on assessing the possibility to merge machine learning algorithms and error-correcting codes together.

KAIST-SK AI Research Center (2019 - 2020)

• • • Funded by, SK hynix Inc.

    • My research part is focused on developing key machine learning algorithms for automated vehicle system including semantic segmentation and multi-modal learning.

Research on Adaptive Machine Learning Technology Development for Intelligent Autonomous Digital Companion (2016 - 2020) [Link]

• • • Funded by, ICT R&D program of Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIP)

    • My research part is focused on developing meta-learning algorithms for an intelligent autonomous digital companion. As results, the meta-learner with linear nulling is proposed.

    • Academic results: 1 paper for few-shot learning in ICML 2019, 1 workshop paper in meta-learning workshop at NIPS 2018 (NeurIPS)

Cloud Storage Coding (2016 - 2019)

• • • Funded by,  National Research Foundation of Korea government

    • My research part is focused on mathematical analysis of storage capacity & security issue in clustered distributed storage system (partial contribution as a co-author).

    • Academic results: 1 conf. paper for the security issue / 1 journal & 1 conf. paper for the analysis on the capacity of clustered distributed storage

KAIST-SK hynix Storage Media Solutions Center (2013 - 2020)

• • • Funded by, SK hynix Inc.

    •  My research part is focused on the high-performance and low-complexity algorithm/hardware of error correcting codes for NAND ash memory.

    • Academic results: 1 conf. paper for low-complexity concatenated polar coding algorithm for storage