Brief Bio

Jinseok Seol received Ph.D. degree in computer science and engineering from Seoul National University, B.S. degree in mathematics and computer science from Yonsei University.

Research Interest

context-aware recommendation models, sequential recommendation models, anomaly detection, parameter-efficient deep learning models, cross-domain visual search, and explainable artificial intelligence.

Publication

[1] * Jinseok Seol, Minseok Gang, Sang-goo Lee, Jaehui Park * Proxy-based Item Representation for Attribute and Context-aware Recommendation * International Conference on Web Search and Data Mining (WSDM), 2024.

[2] * Hanbit Lee, Jinseok Seol, Sang-goo Lee, Jaehui Park, Junho Shim * Contrastive Learning for Unsupervised Image-to-Image Translation * Applied Soft Computing 151, 2024.

[3] * Jinseok Seol, Youngrok Ko, Sang-goo Lee * Exploiting Session Information in BERT-based Session-aware Sequential Recommendation * International Conference on Research and Development in Information Retrieval (SIGIR), Short Paper Track, 2022.

[4] * Jinseok Seol, Seongjae Kim, Sungchan Park, Holim Lim, Hyunsoo Na, Eunyoung Park, Dohee Jung, Soyoung Park, Kangwoo Lee, Sang-goo Lee * Technologies for AI-Driven Fashion Social Networking Service with E-Commerce * International Semantic Intelligence Conference (ISIC), The Applications and Deployment Track, 2022.

[5] * Hyunsoo Cho, Jinseok Seol, Sang-goo Lee * Masked Contrastive Learning for Anomaly Detection * International Joint Conferences on Artificial Intelligence Organization (IJCAI), 2021.

[6] * Sanghyuk Choi, Taeuk Kim, Jinseok Seol, Sang-goo Lee * A Syllable-based Technique for Word Embeddings of Korean Words * Proceedings of the 1st Workshop on Subword and Character Level Models in NLP (SCLeM), EMNLP Workshop, 2017.

Working Experience

IntelliSys Corp. (2018.09 – 2020.09)

Contact

* email: jsseol@kaist.ac.kr

* github: https://github.com/theeluwin