SAIL

Scalable Artificial Intelligence Laboratory

Yong-Hyuk Moon is an Assistant Professor of Computer Engineering at Sungshin Women's University. Our mission is to push the boundaries of task-agnostic models toward self-evolving AI through research on reasoning trajectories, efficient architectures, model optimization and compression, and on-device adaptation.

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Current Activities

We are currently building our lab website and look forward to sharing exciting updates soon. April 2026 Update

Two papers have been submitted to ASK 2026 and are currently under review. April 2026

🎉 Excited to share that two papers have been accepted to AVSS 2026. March 2026 Neural Network Rescaling Memory-Constrained Pruning

Prof. Yong-Hyuk Moon served as a reviewer for NeurIPS 2026. March 2026

Prof. Yong-Hyuk Moon served as a reviewer for BMVC 2026. March 2026

Our joint work with CNU has been accepted for publication in CVIU. March 2026 Computer Vision and Image Understanding Spatial-Temporal ReID

Prof. Yong-Hyuk Moon served as a reviewer for ECCV 2026. February 2026

Prof. Yong-Hyuk Moon served as a reviewer for CVPR 2026. February 2026

Our joint work with JBNU has been accepted for publication in Applied Sciences. January 2026 Applied Sciences Efficient AI Systems

Pleased to share that one paper has been accepted for publication in KTSDE. December 2025 Transactions of the Korea Information Processing Society Channel Pruning

🎉 Our undergraduate student paper won the Bronze Award at ACK 2026. May 2025 Filter Pruning KIPS

Pleased to share that three papers have been accepted to ACK 2026. April 2025 Augmented Sampling | CNN Pruning | BERT KD KIPS

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Publications

* Corresponding author

BayPOS: Bayesian Pareto-Optimal Scaling for Sparse Learning Yong-Hyuk Moon
AVSS 2026 (Accepted) Model Rescaling [Paper] [Project]

Memory-Constrained Pruning via Hybrid Gradient–Curvature Optimization Hyunsoo Lee, Yong-Hyuk Moon*
AVSS 2026 (Accepted) Model Pruning [Paper] [Project]

Object Re-identification via spatial–temporal fusion networks and causal identity matching Hye-Geun Kim, Yong-Hyuk Moon, Yeong-Jun Cho
Computer Vision and Image Understanding Joint Work with CNU Spatial-Temporal Re-identification [Paper] [Project]

A Carbon-Efficient Framework for Deep Learning Workloads on GPU Clusters Dong-Ki Kang, Yong-Hyuk Moon*
Applied Sciences Efficient AI Systems [Paper] [Project]

Adaptive Filter Pruning via One-Shot Ratio Search and In-Training Sparsity Scheduling Hyunsoo Lee, Yong-Hyuk Moon*
KTSDE (Accepted) One-Shot Pruning [Paper] [Project]

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