I am working for the Biomedical Informatics Center as a Neural Networks Research Assistant in Stony Brook University. My research project is uncertainty estimation for tumor prediction. I am also very interested in Neural Network Optimization. Previously, I worked as Deep Learning Engineer for the Dept of Space Weather in the Republic of Korea Air Force and Ninewatt Seoul. Currently, I am an undergraduate student majoring in Computer Science and Applied Mathematics at Stony Brook University.

Deep learning, Optimization, Neural Networks, Quantization, Medical Image Analysis, Learning Theory

[Paper Accepted at 12.08.2024]
One paper entitled 'ZNorm: Z-Score Gradient Normalization Accelerating Skip-Connected Network Training without Architectural Modification' was accepted in the workshop, AAAI 2025 - The 39th Annual AAAI Conference on Artificial Intelligence - Workshops. [Paper]

[Paper Accepted at 11.18.2024]
One paper entitled 'Mitigating Gradient Overlap in Deep Residual Networks with Gradient Normalization for Improved Non-Convex Optimization' was accepted in the workshop, IEEE BigData 2024 - IEEE International Conference on Big Data - Workshops. [Paper]

[Paper Accepted at 06.28.2024]
One paper entitled 'Analysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and ARIMA-LSTM Networks, SPAICE 2024 - The First Joint European Space Agency/IAA Conference on AI in and for Space (Main conference). [Paper]

[Paper Accepted at 04.10.2024]
One paper entitled 'Uncertainty Estimation for Tumor Prediction with Unlabeled Data' was accepted in the workshop, CVPRW 2024 - IEEE/CVF Conference on Computer Vision and Pattern Recognition - Workshops. [Paper]

[Paper Accepted at 03.15.2024]
One paper entitled 'Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks' was accepted in the conference, IJCNN 2024 - International Joint Conference on Neural Network (Main conference). [Paper]