Ph.D. in Computer Science and Engineering
- 2014, Sogang University, Computer Science and Engineering, B.S.
- 2019, POSTECH, Computer Science and Engineering, Ph.D.
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 Mining, Machine Learning, Deep Learning, and Artificial Intelligence, and their applications including but not limited to the following:
Social network analysis
Graph representation learning
Node classification / Link prediction
Time-series and spatio-temporal anlaysis,
- Chanyoung Park, Jiawei Han, Hwanjo Yu (2020. 6) "Deep Multiplex Graph Infomax: Attentive Multiplex Network Embedding using Global Information". Knowledge-Based Systems (SCI) (IF. 5.910)
- Chanyoung Park, Donghyun Kim, Min-Chul Yang, Jung-Tae Lee, Hwanjo Yu (2020. 6) "Click-aware Purchase Prediction with Push at the Top". Information Sciences (SCI) (IF. 5.912)
- Chanyoung Park, Donghyun Kim, Hwanjo Yu (2019. 12) "An Encoder-Decoder Switch Network for Purchase Prediction". Knowledge-Based Systems (SCI) (IF. 5.910)
- Chanyoung Park, Donghyun Kim, Jinoh Oh, Hwanjo Yu (2016. 12) "Improving top-K recommendation with truster and trustee relationship in user trust network". Information Sciences (SCI) (IF. 5.912)