Postdoctoral Researcher at the Korea Advanced Institute of Science and Technology (KAIST). I am the developer of KARINA, the first deep learning-based global weather forecast model in Korea.
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<aside> βοΈ jmj2316@kaist.ac.kr
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Nov 2024 - Present
Mar 2023 - Oct 2024
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
Korea Institute of Science and Technology (KIST), Seoul, Korea
2023
2020
2017-2018
Ph.D., Department of Information System, Hanyang University, Seoul, Korea (M.S.-Ph.D. combined)
B.S., Department of Information System, Hanyang University, Seoul, Korea
Exchange student, Department of Information Technology, Uppsala University, Sweden
2023-Present
A study on deep learning-based prediction of the tropical intraseasonal oscillation (National Research Foundation of Korea)
Development of an AI global climate prediction system at high-resolution (National Research Foundation of Korea)
2021-2022
System design of autonomous evolutionary online payment service (Korea Ministry of Education)
2024
Cheon, M., Choi, Y. H., Kang, S. Y., Choi, Y., Lee, J. G., & Kang, D*. (2024). KARINA: An Efficient Deep Learning Model for Global Weather Forecast. arXiv preprint arXiv:2403.10555.
Cheon, M., Kang, D.*, Choi, Y. H., & Kang, S. Y. (2024). Advancing Data-driven Weather Forecasting: Time-Sliding Data Augmentation of ERA5. arXiv preprint arXiv:2402.08185.
Mun, C., Ha, H., Lee, O., & Cheon, M.* (2024). Enhancing AI-CDSS with U-AnoGAN: Tackling data imbalance. Computer Methods and Programs in Biomedicine, 244, 107954.
Cheon, M., & Mun, C*. (2024). Combining KAN with CNN: KonvNeXtβs Performance in Remote Sensing and Patent Insights. Remote Sensing, 16(18), 3417.
Cheon, M. (2024). Demonstrating the efficacy of kolmogorov-arnold networks in vision tasks. arXiv preprint arXiv:2406.14916.
Joo, H., Lee, E., & Cheon, M*. (2024). Habaek: High-performance water segmentation through dataset expansion and inductive bias optimization. arXiv preprint arXiv:2410.15794.
Choi, Y., Kang, S., & Cheon, M*. (2024). Advancing Meteorological Forecasting: AI-based Approach to Synoptic Weather Map Analysis. arXiv preprint
2023
Cheon, M. (2023, June). SR-AnoGAN: you never detect alone. super resolution in anomaly detection (student abstract). In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 13, pp. 16194-16195).
Cheon, M., & Mun, C*. (2023). The Climate of Innovation: AIβs Growing Influence in Weather Prediction Patents and Its Future Prospects. Sustainability, 15(24), 16681.
2022
Cheon, M., Ha, H., Lee, O., & Mun, C*. (2022). A Novel Hybrid Deep Learning Approach to Code Generation Aimed at Mitigating the Real-Time Network Attack in the Mobile Experiment Via GRU-LM and Word2vec. Mobile Information Systems, 2022.
Cheon, M., Lee, O., Mun, C., & Ha, H*. (2022). Factors affecting academic achievement in SW education. International Journal of Information and Education Technology, 12(4), 333-338.
Cheon, M., Lee, O., Mun, C., & Ha, H*. (2022). A study on the factors affecting intention of learning Python programming: For non-majors in university. Int. J. Inf. Educ. Technol, 12, 414-420.
Lee, O., Joo, H., Choi, H., & Cheon, M.* (2022). Proposing an integrated approach to analyzing ESG data via machine learning and deep learning algorithms. Sustainability, 14(14), 8745.
2021
Cheon, M. J., Lee, D., Joo, H. S., & Lee, O*. (2021). Deep learning based hybrid approach of detecting fraudulent transactions. Journal of Theoretical and Applied Information Technology, 99(16), 4044-4054.
Cheon, M. J., & Lee, O*. (2021). Detecting olfactory impairment through objective diagnosis: catboost classifier on EEG data. Journal of Theoretical and Applied Information Technology, 99(14), 3596-3604.
Cheon, M. J., Lee, D. H., Park, J. W., Choi, H. J., Lee, J. S., & Lee, O*. (2021). CTGAN VS TGAN? Which one is more suitable for generating synthetic EEG data. Journal of Theoretical and Applied Information Technology, 99(10), 2359-2372.