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Research Topics
Multimodal Learning
combines image, text, audio, touch and etc. to accommodate various learning preferences, enhancing overall comprehension
Domain Adaptation
adapts an AI model from one domain to another, enhancing its performance on related but different data distributionsย
Efficient Model Learning
optimizes an AI model using a small subset of its parameters while minimizing computational costs and memory usageย
Video Understanding
aims to interpret a video scene by recognizing objects, their temporal relationships, and the surrounding events to enable meaningful understanding of the videoย
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Robotics AI
enables robots to understand visual data from their surroundings using cameras and multiple sensors, enhancing their autonomy and versatilityย
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On-going Projects
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Journal Publications
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Conference Publications
Latest News
[Paper] 2026.02 ์ฅ์ ์ง์, ๋ฅํ์ด๋ง, ์ ์ ์ฒ ํ์์ "ZOO-Prune: Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models" ๋
ผ๋ฌธ์ด CVPR 2026์ accept๋์์ต๋๋ค. ์ถํํฉ๋๋ค!
[Member] 2026.02 ๋ผํ์ฌ, ์ ์ ์ฒ, ์ด์นํ ํ์์ด IPIU 2026 ์ฐ์ ํฌ์คํฐ ๋ฐํ์์ ์์ํ์์ต๋๋ค. ์ถํํฉ๋๋ค.
[Paper] 2026.01 ํ์ฑ์ ๊ต์๋์ "Hyper-STTN: Hypergraph Augmented Spatial-Temporal Transformer Network for Trajectory Prediction" ๋
ผ๋ฌธ์ด IEEE International Conference on Robotics & Automation (ICRA) 2026 ํํ์ accept๋์์ต๋๋ค.
[Member] 2025.11 ์ต์์ค ํ์์ด ์์ธ์ฅํ์ฌ๋จ AI์์ธํ
ํฌ ๋ํ์ ์ฅํ์์ผ๋ก ์ ์ ๋์์ต๋๋ค.
[Member] 2025.09 ๋ฅ๋ณด๊ณค, ๊นํ์ฝ ํ์์ด ์ 35ํ ์ธ๊ณต์ง๋ฅ์ ํธ์ฒ๋ฆฌํ์ ๋ํ ์ฐ์ ํฌ์คํฐ ๋ฐํ์์ ์์ํ์์ต๋๋ค. ์ถํํฉ๋๋ค.
[Paper] 2025.09 ์ฐ๊ตฌ์ค ๋
ผ๋ฌธ 2ํธ์ด NeurIPS 2025์ accept๋์์ต๋๋ค. 1. "Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment" (์ฅ์ ์ง์, ๊นํ์ฝ, ๋ฅํ์ด๋ง ํ์ ์ฐธ์ฌ)ย 2. "PRIMT: Preference-based Reinforcement Learning with Multimodal Feedback and Trajectory Synthesis from Foundation Models" (Prof. Byung-Cheol Min @ Purdue Univ. ๊ณต๋ ์ฐ๊ตฌ)
[Member] 2025.09 ์์์ฐ ํ์์ ์์ฌ๊ณผ์ ํฉ๋ฅ์ Josep์ ์๋ฐ์ฌํตํฉ๊ณผ์ ํฉ๋ฅ๋ฅผ ์ถํํฉ๋๋ค.
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Office : 90313, International Hall, Sungkyunkwan University,
25-2 Sungkyunkwan-ro, Jongno-gu, Seoul 03063, Korea
Email : csehong@skku.eduย ย Web : aim.skku.edu ย Tel : 02-740-1809
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