About Me
I am a Ph.D. student at KAIST NMSL, under the guidance of Prof. Sung-Ju Lee, with close collaboration with Prof. Jinwoo Shin. I earned my M.S. in Electrical Engineering from KAIST, also under the supervision of Prof. Sung-Ju Lee. I completed my B.S. in Computing at KAIST, graduating Magna Cum Laude.
My research interests include end-user machine learning, including mobile AI, adaptation, and personalization. I am currently focusing on robust and reliable test-time adaptation without any source or labeled data. My recent work includes “AETTA” (CVPR 2024) and “SoTTA” (NeurIPS 2023), which focus on estimating accuracy during test-time adaptation without labeled data and address the challenges of adapting models to noisy data streams, emphasizing the robustness and reliability of test-time adaptation.
Latest News
Jul 2025 (expected) Research intern at Microsoft Research Asia (Advisor: Lili Qiu).
Feb 2024 First-author paper (AETTA) accepted at CVPR ‘24 (Acceptance rate: 23.6%).
Sep 2023 Co-first-author paper (SoTTA) accepted at NeurIPS ‘23 (Acceptance rate: 26.1%).
Jun 2022 First-author paper accepted at CVPR Workshop (CVPM) ‘22.
Jun 2022 Demo at MobiSys ‘22.
Oct 2020 Selected as a scholarship recipient of the Kwon Yong-se Scholarship (KAIST EE).
Education
Ph.D. Candidate, KAIST
Ph.D. Candidate in School of Electrical Engineering (Advisor: Prof. Sung-Ju Lee)
2022.08 - Present
2020.08 - 2022.08
B.S., KAIST
B.S. in School of Computing
- GPA 3.96/4.30 (Magna Cum Laude), Advanced Major, Certificate in AI
2016.02 - 2020.08
Publications
Taeckyung Lee, Sorn Chottananurak, Junsu Kim, Jinwoo Shin, Taesik Gong^, Sung-Ju Lee^
Under review (^: Equal advising)
"AETTA: Label-Free Accuracy Estimation for Test-Time Adaptation"
[ Project page ] [ Paper ] [ Code ] [ Video ]
Taeckyung Lee, Sorn Chottananurak, Taesik Gong, Sung-Ju Lee
CVPR 2024 (Acceptance rate: 23.6%)
"SoTTA: Robust Test-Time Adaptation on Noisy Data Streams"
[ Project page ] [ Paper ] [ Code ] [ Video ]
Taesik Gong*, Yewon Kim*, Taeckyung Lee*, Sorn Chottananurak, Sung-Ju Lee
NeurIPS 2023 (* Co-first author. Acceptance rate: 26.1%)
Taeckyung Lee, Dain Kim, Sooyoung Park, Dongwhi Kim, Sung-Ju Lee
CVPR Workshops 2022 (Oral presentation, peer-reviewed, archived)
- Also appeared at MobiSys 2022 Demo
Work Experiences
2025.07 - 2025.12 (expected)
Networking and Mobile Systems Lab, KAIST
Undergraduate Researcher
2020.03 - 2020.08
Deepscent
Software Engineer Intern
2019.12 - 2020.02
Advanced Networking Lab, KAIST
Undergraduate Researcher
2019.03 - 2019.12
Awards
Kwon Young-se Scholarship
School of EE, KAIST (Top-2 among EE grad school applicants in 2020 Fall)
2020.10.12
The National Scholarship for Science and Engineering
Ministry of Science and ICT, Korean Government (In acknowledgment of a high GPA)
2018.08.10
Professional Services
Reviewer
- ICCV ‘25
- ICML ‘25
- CVPR ‘24, ‘25
- ICLR ‘25
- NeurIPS ‘24
Teaching Experiences
Teaching Assistant @ KAIST
- EE209 Programming Structures for EE (Spring 2025 (Head TA), Fall 2024, Spring 2023 (Head TA), Fall 2021 (Head TA))
- EE323 Computer Networks (Spring 2024, Spring 2022, Spring 2021)
- EE415 Operating Systems and System Programming for EE (Fall 2023)
- EE595 Mobile Computing, Sensing, Learning, and Interactions (Fall 2022)
- CS496 Immersion Camp (Summer 2019)
Patents
UWB-based Pedestrian Collision Avoidance System for Personal Mobility Devices
Sung-Ju Lee, Taeckyung Lee, Hyungjun Yoon, Seungjoo Lee, Hyeongheon Cha
Korea Patent, Filing date: 2025.02.12, No.10-2025-0018095
Time-Aware Reinforcement-Learning Method for Geographic Ad Hoc Routing with Pre-defined Mobility
Jaeha Ahn, Sung-Ju Lee, Taesik Gong, Hyungjun Yoon, Taeckyung Lee
Korea Patent; Date of patent: 2024.12.02, No.10-2738891, Filing date: 2022.11.11, No.10-2022-0150662
Reinforcement Learning for Ad-hoc Routing Using Pre-defined Mobility
Sung-Ju Lee, Taesik Gong, Hyungjun Yoon, Taeckyung Lee, Jaeha Ahn
Korea Patent; Date of patent: 2024.04.22, No.10-2660836, Filing date: 2022.03.21, No.10-2022-0034824
Miscellaneous
E-Sports
As a previous enthusiastic e-sports player, I am also interested in human factors in e-sports.
Analysis on Personality and In-Game Factors in League of Legends (Link)
- I conducted an in-depth analysis of the personalities and in-game factors of League of Legends players through a collaborative survey with the Professional Spectator YouTube channel.
Few records as a player:
- Top 0.1% Player (Master tier) in KR Server, League of Legends (2020)
- Champion in Daejeon Metropolitan City, International e-Sports Festival (IEF), League of Legends (2019)
- Top-500 Player in KR Server, Overwatch (2017)