Announcements
Life
[05.2025] I will be joining the University of Southern California for the MSCS program starting in Fall 2025
[05.2025] Officially Graduated from Stony Brook University!
[09.2023] Joined Biomedical Informatics Center at Stony Brook University
[05.2022] Joined Data and Intelligent Computing Lab at Stony Brook University
[08.2020] Served my military duty at Republic of Korea Air Force Headquarters as a Deep Learning Engineer
Open Neural Network Research Lab
[05.2025] Two papers were submitted to a ML conference (Core Rank: A) by OpenNN Lab
Sharpness-Aware Minimization with Z-Score Gradient Filtering for Neural Networks
[Paper]Spectral and Temporal Denoising for Differentially Private Optimization
[Paper][01.2025] Launched the Open Neural Network Research Lab, supported by the Brian Impact Foundation
Eleven researchers from global research institutions joined the lab
[Read More]Publications
[05.2025] One paper was accepted at Neural Computing and Application (IF: 4.5)
Stochastic Gradient Sampling for Enhancing Neural Networks Training
[Paper][04.2025] One paper was submitted to a ML conference (Core Rank: B)
Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited Learning
[Paper][12.2024] One paper was accepted at AAAI 2025 Workshops
ZNorm: Z-Score Gradient Normalization Accelerating Skip-Connected Network Training without Architectural Modification
[Paper][11.2024] One paper was accepted at IEEE BigData 2024
Mitigating Gradient Overlap in Deep Residual Networks with Gradient Normalization for Improved Non-Convex Optimization
[Paper][07.2024] One paper was accepted at European Space Agency (ESA) SPAICE 2024
Analysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and ARIMA-LSTM Networks
[Paper][04.2024] One paper was accepted at CVPR 2024 Workshops
Uncertainty Estimation for Tumor Prediction with Unlabeled Data
[Paper][03.2024] One paper was accepted at IJCNN 2024
Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
[Paper]Hackathon/Contents
[04.2025] Got 3rd place at Stony Brook Web Development Hackathon 2025
Joined as a full-stack engineer [React] [Node] [Express] [MongoDB]
[10.2023] Got 1st place at Data Science Track of NYC Hack-O-Ween Hackathon 2023
Joined as a deep learning engineer [pyTorch] [Python] [OpenCV]
[07.2022] Got 3rd place at Microsoft Hackerground Hackathon 2023
Joined as a deep learning engineer [pyTorch] [Python]
[05.2022] Got 1st place at Stony Brook SUNY Korea Hackathon 2023
Joined as a deep learning engineer [TensorFlow] [Python]
[05.2021] Got 3rd place at Korea Daegu City Public Datathon 2021
Joined as a deep learning engineer [TensorFlow] [Python]
[04.2021] Got 3rd place at Korea Smart City Data Hackathon 2021
Joined as a data scientist [React] [Node] [Express] [MongoDB]
[07.2019] Got 1st place at Busan Pathhack/Google Developer Groups Hackathon 2019
Joined as a full-stack engineer [C#] [.Net] [GCP]
[07.2019] Got 1st place at Contributor MVP Award of COSMOS Hackathon Seoul 2019
Joined as a full-stack engineer [C#] [.Net] [GCP]
[08.2018] Got 3rd place at Global Applied Game Jam 2018
Joined as a C# and Unity Programmer [C#] [Unity3D]
Advising/Mentoring