Hi, I’m a master’s student in the Graduate school of AI at KAIST (MLAI Lab), where I am fortunate to be advised by Prof. Sung Ju Hwang. I am interested in Machine Learning for Graphs. Prior to studying at KAIST, I obtained my B.S. (Computer Science and Engineering) and B.E. (Software Technology and Enterprise Program) degrees at Korea University.
Also, I was a technical director of Jobshopper ((주)잡쇼퍼), an AI-based education startup company in Seoul, Korea. During one year of full-time work experience at Jobshopper as a lead engineer and researcher, I led the development and research groups of more than 10 people. Now, I am technically advising Jobshopper, as well as MajorMap (메이저맵(주)) spin-offed from Jobshopper.
My research interest is mainly on developing novel machine learning models and algorithms for graphs.
I recently focus on following three topics:
1) representing or generating graph-structured data such as a molecule, society, and neural network,
2) modeling interactions between knowledge from relational-structured or even raw data with graphs,
3) and tackling challenges on real-world graphs having noise or temporality.
KAIST (Korea Advanced Institute of Science and Technology)
- M.S. student in Artificial Intelligence, Mar 2020 - Present.
- GPA: 4.22 / 4.30 (99.1 / 100)
- Bachelor of Science in Computer Science and Engineering, Mar 2016 - Feb 2020.
- Bachelor of Engineering in Software Technology and Enterprise Program (Interdisciplinary Program), Aug 2017 - Feb 2020.
- GPA: 4.40 / 4.50 (98.9 / 100), GPA of Computer Science and Engineering: 4.48 / 4.50 (99.5 / 100)
* denotes the equal contribution.
- Jaehyeong Jo*, Jinheon Baek*, Seul Lee*, Dongki Kim, Minki Kang, and Sung Ju Hwang. Edge Representation Learning with Hypergraphs. Conference on Neural Information Processing Systems (NeurIPS), 2021. [paper]
- Wonyong Jeong*, Hayeon Lee*, Gun Park*, Eunyoung Hyung, Jinheon Baek, and Sung Ju Hwang. Task-Adaptive Neural Network Retrieval with Meta-Contrastive Learning. Conference on Neural Information Processing Systems (NeurIPS), 2021. (Spotlight Presentation) [paper]
- Jinheon Baek*, MinKi Kang*, and Sung Ju Hwang. Accurate Learning of Graph Representations with Graph Multiset Pooling. International Conference on Learning Representations (ICLR), 2021. [paper] [code]
- Jinheon Baek, Dong Bok Lee, and Sung Ju Hwang. Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction. Conference on Neural Information Processing Systems (NeurIPS), 2020. [paper] [code]
- Hyunjae Kim*, Yookyung Koh*, Jinheon Baek, and Jaewoo Kang. Exploring The Spatial Reasoning Ability of Neural Models in Human IQ Tests. Neural Networks, 2021. [paper]
- Soyeong Jeong, Jinheon Baek, ChaeHun Park, and Jong C. Park. Unsupervised Document Expansion for Information Retrieval with Stochastic Text Generation. Scholarly Document Processing at Conference of the North American Chapter of the Association for Computational Linguistics (SDP@NAACL), 2021. (Oral Presentation) [paper]