Research Interests

• Statistical Learning

• Fintech (portfolio optimization & quantitative investment)

Publications (Int'l. Journal & Int'l. Conference, 📄: paper, 🌐: project repo, *: corresponding author, †: co-first author, _: lab. member)

1. Variational AutoEncoder for Distributional Learning via Quantile Function Estimation. 📄 (Generative Model)
   S An, S Hong, and J-J Jeon*. Neural Networks, 2025.

2. Improving SMOTE via Fusing Conditional VAE for Data-adaptive Noise Filtering. 📄 (Generative Model + Skewed Dataset)
   S Hong, S An, and J-J Jeon*. Applied Intelligence, 2025.

3. Dynamic High-Order Relations and Event-Driven Temporal Modeling for Stock Price Forecasting. 📄 (GNN + Finance)
   K Park, S Hong, and J-J Jeon*. The 34th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Canada, 2025.

4. Adaptive Adversarial Augmentation for Molecular Property Prediction. 📄 🌐 (GNN + Molecular Data)
   S Cho, S Hong, and J-J Jeon*. Expert Systems with Applications, 2025.

5. Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis. 📄 🌐 (LLM + Tabular Data)
   S An, G Woo, J Lim, C Kim, S Hong, and J-J Jeon*. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), Philadelphia, USA, 2025.

6. Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms. 📄 🌐 (Time Series + XAI)
   S Hong, Y Choi, and J-J Jeon*. International Journal of Forecasting, 2024.

7. Cryptocurrency Price Forecasting Using Variational Autoencoder with Versatile Quantile Modeling. 📄 🌐 (Time Series + Generative Model)
   S Hong, S An†, and J-J Jeon*. The 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, USA,  2024.

8. Sparse Kernel K-means Clustering. 📄 (Machine Learning)
   B Park, C Park, S Hong, and H Choi*. Journal of Applied Statistics, 2024.

9. Finding an NARE whose minimal nonnegative solution represents first passage quantities in the two-dimensional Brownian motion. 📄 (Stochastic Process)
   S Hong and S Ahn*. Journal of the Korean Statistical Society, 2024.

10. Clustering for Regional Time Trend in the Nonstationary Extreme Distribution. 📄 🌐 (Machine Learning + Hydrology)
    S Hong, J-J Jeon*, and Y Kim. Water, 2022.

11. Application of GTH-like algorithm to Markov modulated Brownian motion with jumps. 📄 (Stochastic Process)
    S Hong and S Ahn*. Communications for Statistical Applications and Methods, 2021. 

Preprints/Submitted

• Uniform Pessimistic Risk and its Optimal Portfolio. 📄 (Machine Learning + Finance)
  S Hong and J-J Jeon*. preprint.

• Unicorn: U-Net for Sea Ice Forecasting with Convolutional Neural Ordinary Differential Equations. 📄 (Time Series + Geoscience)
  J Park, Y Cho, J-J Jeon, J Park, H-Y Kim, and S Hong*. preprint,  under revision in Scientific Reports.

• Monotone Composite Quantile Regression via Second-Order Gradient Boosting Framework. (Quantile Regression)
  S Moon, S Hong†, and B Park*. under review.

• Deep Generative Model for Time-series Forecasting. (Time Series + Generative Model)
  S An, S Hong†, and J-J Jeon*. under review.

In Progress 

• Enhanced Gradient Boosting Decision Tree for Financial Imbalanced Datasets. (Machine Learning + Finance)
  S Hong and B Park*

• LLM-RAG System for Molecular Property Prediction. (LLM + Molecular Data)
  I Jung and S Hong*

• Time Series Anomaly Detection via Robust Variational Autoencoder.  (Time Series + Generative Model)
  S Hong.

• Aggregated Loss for Multivariate Probabilistic Forecasting.  (Time Series + Generative Model)
  S Hong.

Presentations

• 2025

1. VAE for Financial Data Analysis. KAIA (한국인공지능학회) Summer Conference, Phoenix Park, Aug 8. 

2. Deep Generative Model for Time Series. Dept. of Information & Statistics@GNU (경상국립대학교). Jan 17. 

• 2024 

  1. VAE-based Probabilistic Forecasting. Dept. of Statistics@CAU (중앙대학교). Dec 13. 

  2. Cryptocurrency Price Forecasting using Variational AutoEncoder with Versatile Quantile Modeling. CIKM 2024. Boise Center, Boise, USA, Oct 23.

  3. Cryptocurrency Price Forecasting using Variational AutoEncoder with Versatile Quantile Modeling. KDAS (한국자료분석학회), University of Seoul, Jun 28.

• ~ 2023 

  1. Interpretable Spatio-Temporal Transformer for Water Level Forecasting. KDAS (한국자료분석학회), Busan, Jan 27, 2023.

  2. Uniform Pessimistic Risk and its Applications (spotlight (우수상)). KAIA & NAVER Joint Conference (한국인공지능학회 & NAVER 공동학술대회), NAVER, Nov 18, 2022. 

  3. Forecasting Tail Risk of Time Series with Weighted Scoring Rules. KDAS (한국자료분석학회), Sungshin Women's University, Jul 8, 2022.

  4. Uniform pessimistic risk and optimal portfolio. KDISS (한국데이터정보과학회), Pusan National University, May 13, 2022.

  5. Grouped portfolio optimization with pessimistic risk measure. CMStatistics 2019, University of London, Dec 15, 2019.

  6. Grouped portfolio optimization with pessimistic risk measure. KSS (한국통계학회), University of Seoul, Nov 9, 2019