Our lab focuses on distributional learning in the tabular and time-series domains and its applications to real-world problems. We are particularly interested in the following areas:
Tabular Data Synthesis
Density Estimation
Time-Series Forecasting
In future research, we plan to explore:
(Time-Series) Anomaly Detection
Data Augmentation
Missing Data Imputation
Federated Learning
We also welcome students who are interested in applying big data, statistical, and machine learning methodologies to analyze datasets of their choice. If you have a dataset you’d like to explore using advanced analytical techniques, or if you’re interested in distributional learning and its applications, please feel free to reach out.
For any inquiries, please email sh.an@inu.ac.kr, including a short transcript and your CV.
[2025-08-08] I will be giving a talk at the 2025 한국인공지능학회 하계학술대회 - 기획세션 (AI and Statistics)
- @ 평창 휘닉스파크, 휘닉스호텔 (25.08.07 - 25.08.08)
- Topic: Distribution Estimation with Generative Model and its Applications: Tabular Data, Time Series
[2025-08-04] Our paper has been accepted to Neural Networks (SCIE, IF 6.3, Q1)!
[2025-06-01] Our paper has been accepted to Applied Intelligence (SCIE, IF 3.5, Q2)!
[2025-05-29] I will be giving a talk at the 2025 KIAS CAINS Workshop!
- @ Park Roche Resort, Jeongseon (25.05.28 - 25.05.30)
- Topic: Distributional Learning for Tabular Data Synthesis
e-mail: sh.an@inu.ac.kr
Tel: 032-835-8632
Address: Rm. 226, Bldg. 7, 119 Academy-ro, Yeonsu-gu, Incheon 22012, South Korea