| 2023 | HAIS | A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand. | Seok-Jun Bu, Sung-Bae Cho |
| 2022 | HAIS | Evolutionary Triplet Network of Learning Disentangled Malware Space for Malware Classification. | Kyoung-Won Park, Seok-Jun Bu, Sung-Bae Cho |
| 2022 | HAIS | A Neuro-Symbolic AI System for Visual Question Answering in Pedestrian Video Sequences. | Jaeil Park, Seok-Jun Bu, Sung-Bae Cho |
| 2021 | HAIS | Evolutionary Optimization of Neuro-Symbolic Integration for Phishing URL Detection. | Kyoung-Won Park, Seok-Jun Bu, Sung-Bae Cho |
| 2021 | ICASSP | Integrating Deep Learning with First-Order Logic Programmed Constraints for Zero-Day Phishing Attack Detection. | Seok-Jun Bu, Sung-Bae Cho |
| 2021 | IDEAL | Directional Graph Transformer-Based Control Flow Embedding for Malware Classification. | Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho |
| 2021 | IDEAL | Learning Dynamic Connectivity with Residual-Attention Network for Autism Classification in 4D fMRI Brain Images. | Kyoung-Won Park, Seok-Jun Bu, Sung-Bae Cho |
| 2020 | ICASSP | A Monte Carlo Search-Based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear. | Seok-Jun Bu, Namu Park, Gue-Hwan Nam, Jae-Yong Seo, Sung-Bae Cho |
| 2020 | ICASSP | Data Augmentation Using Empirical Mode Decomposition on Neural Networks to Classify Impact Noise in Vehicle. | Gue-Hwan Nam, Seok-Jun Bu, Namu Park, Jae-Yong Seo, Hyeon-Cheol Jo, Won-Tae Jeong |
| 2020 | ICDM | Learning Disentangled Representation of Residential Power Demand Peak via Convolutional-Recurrent Triplet Network. | Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho |
| 2020 | IDEAL | Automated Learning of In-vehicle Noise Representation with Triplet-Loss Embedded Convolutional Beamforming Network. | Seok-Jun Bu, Sung-Bae Cho |
| 2020 | IDEAL | A Deep Metric Neural Network with Disentangled Representation for Detecting Smartphone Glass Defects. | Gwang-Myong Go, Seok-Jun Bu, Sung-Bae Cho |
| 2019 | HAIS | Genetic Algorithm-Based Deep Learning Ensemble for Detecting Database Intrusion via Insider Attack. | Seok-Jun Bu, Sung-Bae Cho |
| 2019 | IDEAL | A Deep Learning-Based Surface Defect Inspection System for Smartphone Glass. | Gwang-Myong Go, Seok-Jun Bu, Sung-Bae Cho |
| 2018 | HAIS | A Hybrid Deep Learning System of CNN and LRCN to Detect Cyberbullying from SNS Comments. | Seok-Jun Bu, Sung-Bae Cho |
| 2018 | HAIS | Hybrid Deep Learning Based on GAN for Classifying BSR Noises from Invehicle Sensors. | Jin-Young Kim, Seok-Jun Bu, Sung-Bae Cho |
| 2018 | IDEAL | Learning Optimal Q-Function Using Deep Boltzmann Machine for Reliable Trading of Cryptocurrency. | Seok-Jun Bu, Sung-Bae Cho |
| 2017 | HAIS | A Hybrid System of Deep Learning and Learning Classifier System for Database Intrusion Detection. | Seok-Jun Bu, Sung-Bae Cho |
| 2017 | ICONIP | Malware Detection Using Deep Transferred Generative Adversarial Networks. | Jin-Young Kim, Seok-Jun Bu, Sung-Bae Cho |