About Me
Research Interest : Graph Mining, Social Network Analysis, Data Mining, and Machine Learning
I am a M.S. & Ph.D. student in the Graduate School of AI at KAIST. I am very fortunate to be advised by Prof. Kijung Shin. I received my B.S. in Computer Science from Hanyang University.
Education
M.S. & Ph.D. in Artificial Intelligence
KAIST, Seoul, Korea (Mar. 2020 - Feb. 2025 (expected))
B.S. in Computer Science
Hanyang University, Seoul, Korea (Mar. 2016 - Feb. 2020)
Publications
Published Papers
- [W1] Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
Jihoon Ko*, Kyuhan Lee*, Hyunjin Hwang, and Kijung Shin
SSTDM 2022
[ paper | slides | code and datasets | bib ] - [C6] Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications
Shinwhan Kang, Kyuhan Lee, and Kijung Shin
IEEE ICDE 2022
[ paper | appendix | video | slides | code and datasets | bib ] - [J1] Effective Training Strategies for Deep Learning-Based Precipitation Nowcasting and Estimation
Jihoon Ko*, Kyuhan Lee*, Hyunjin Hwang*, Seok-Geun Oh, Seok-Woo Son, and Kijung Shin
Computers & Geosciences
[ paper | code and datasets | bib ] - [C5] Are Edge Weights in Summary Graphs Useful? - A Comparative Study
Shinwhan Kang, Kyuhan Lee, and Kijung Shin
PAKDD 2022
[ paper | appendix | code and datasets | bib ] - [C4] SLUGGER: Lossless Hierarchical Summarization of Massive Graphs
Kyuhan Lee*, Jihoon Ko*, and Kijung Shin
IEEE ICDE 2022
[ paper | appendix | video | slides | code and datasets | bib ] - [C3] DPGS: Degree-Preserving Graph Summarization
Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, and Xueqi Cheng
SIAM SDM 2021 (Acceptance Rate = 21.25% (85/400))
[ paper | code and datasets | bib ] - [C2] MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Social Networks
Jihoon Ko, Kyuhan Lee, Kijung Shin, and Noseong Park
IEEE/ACM ASONAM 2020 (Acceptance Rate = 17.8%)
[ paper | slides | code and datasets | bib ]
Selected for fast-track journal invitation
- [C1] SSumM: Sparse Summarization of Massive Graphs
Kyuhan Lee*, Hyeonsoo Jo*, Jihoon Ko, Sungsu Lim, and Kijung Shin
ACM SIGKDD 2020 (Acceptance Rate = 16.9% (216/1279))
[ paper | video (short) | video (long) | slides | code and datasets | bib ]
Patents
- Method and System for Sparse Summarization of Massive Graphs
Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, and Kijung Shin
Korean Patent 10-2429040 - Method and System for Personalized Summarization of Graphs
Shinwhan Kang, Kyuhan Lee, and Kijung Shin
Korean Patent Application 10-2023-0037867 - Method Computer Device, and Computer Program for Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, and Kijung Shin
Korean Patent Application 10-2022-0136274 - Method and Apparatus for Effective Training for Deep Learning-based Precipitation Nowcasting and Estimation
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang, and Kijung Shin
Korean Patent Application 10-2021-0105149
Registered Patent
Patent Applications
Teaching
- KAIST AI503 Mathematics for AI
Teaching Assistant [Fall 2023]
- KAIST AI617 Machine Learning for Robotics
Teaching Assistant [Spring 2022]
- KAIST AI506 Data Mining and Search
Teaching Assistant [Spring 2021]
- KAIST AI607 Graph Mining and Social Network Analysis
Teaching Assistant [Fall 2021, Fall 2022]
Awards & Honors
- National Science & Technology Scholarship, KOSAF (Mar. 2016 - Feb. 2020)
Full tuition exemptions for 8 semesters. - Summa Cum Laude Graduation Honors, Hanyang University (Feb. 2020)
Skills
Languages
- Korean (mother tongue), English (fluent) - TOEIC 965
Programming Languages
- Working knowledge of various computer languages such as Python, Java, R, and C/C++
- Proficient in back-end development using Node.js, MongoDB and MariaDB
- Proficient with Pytorch and Tensorflow