DSAIL character

Welcome!

We are Data Science & Artificial Intelligence Lab (DSAIL) at KAIST led by Prof. Chanyoung Park. Due to the recent expansion of social media and online communities, online platforms in the digital economy are inundated with vast amounts of usergenerated multimodal (heterogeneous) data from various sources, which can be categorized into structured (e.g., graphs such as social network) and unstructured data (e.g., text, image, video, and audio). When properly analyzed, such multimodal data can be a valuable asset to the companies, but it is challenging not only due to the difficulty in extracting meaningful information from the inherently sparse and noisy data, but also in combining and customizing the extracted knowledge from different modalities with different statistical properties to facilitate various target applications.

Research Area

Our goal is to mine meaningful knowledge from multimodal data, and develop artificial intelligence solutions for various real-world applications across different disciplines. Two underlying themes of our research are:

  1. Representation: How can we extract knowledge from different modalities of data and represent them in a unified way such that the relations among different modalities are captured, and the synergy within the multimodality is facilitated?
  2. Fusion: How can we combine the extracted knowledge and customize it to facilitate various underlying target applications?

Our main research interests include Data-centric AI, Machine Learning, Deep Learning, Multi-modal Data Mining, and their applications including but not limited to the following:

  • Recommender system
  • AI for Science (Chemistry/Bioinformatics/Materials Science)
  • Graph Neural Network and its Applications
  • Molecular design and Drug discovery
  • (Multi-modal) Representation learning
  • Large Language Models
  • Explainable AI
  • Robust machine learning
  • Scene understanding
  • Knowledge graphs
  • Continual learning
  • Causal learning
  • Social network analysis
  • Graph mining
  • Fraud/Anomaly detection
  • Sentiment analysis
  • Purchase/Click prediction
  • Time-series and spatio-temporal analysis,
  • AI for finance
  • etc…

News

May 2024

Two papers got accepted at KDD 2024.

May 2024

A paper got accepted at ICML 2024.

April 2024

We are looking for interns to join our group during this Summer break (8 weeks).

April 2024

A paper got accepted at Briefings in Bioinformatics.

April 2024

Yeonjun started a research internship at Adobe Research, USA.

March 2023

A paper got accepted at WWW 2024 Workshop on Data-centric Artificial Intelligence (DCAI).

February 2024

A paper got accepted at CVPR 2024.

January 2024

Congratulations! Sangwoo Seo and Sungwon Kim received Gold Prize at the 30th Samsung Humantech Paper Award.

January 2024

Two papers got accepted at WWW 2024.

See all news →