Hello! I am a first-year Ph.D. student in CS at the University of Southern California.
My research interest lies in graph mining, knowledge graphs, and machine learning.
I am fortunate to be advised by Prof. Xiang Ren and supported by KEF Scholarship. I received B.S. in Electrical and Computer Engineering at Seoul National University. My undergraduate research was advised by Prof. U Kang.
Research Intern, Creative Innovation Center, LG electronics
Activity Prediction from Sensor Data using Convolutional Neural Networks and an Efficient Compression Method Woojeong Jin, Dongjin Choi, Youngjin Kim, and U Kang
Journal of KIISE, 2018.
[ paper ]
Fast and Accurate Random Walk with Restart on Dynamic Graphs with Guarantees
Minji Yoon, Woojeong Jin, and U Kang
The Web Conference (WWW) 2018, Lyon, France
[ paper ] (14.8% Acceptance Rate)
Ranking in Signed Social Networks: Model and Algorithms
Jinhong Jung, Woojeong Jin, U Kang, and Lee Sael
Knowledge and Information Systems (KAIS) (under revision)
[ paper | www (code and data) ]
Personalized Ranking in Signed Networks using Signed Random Walk with Restart
Jinhong Jung, Woojeong Jin, Lee Sael, and U Kang
IEEE International Conference on Data Mining (ICDM) 2016, Barcelona, Spain
[ paper | supplement | www (code and data) ] (19.6% Acceptance Rate)
Recommender System based on Graph Ranking using Random Walk Woojeong Jin, Jinhong Jung, and U Kang
Communications of the Korean Institute of Information Scientists and Engineers (KIISE), 2016
[ paper ]
Method for Providing Supervised and Extended Restart in Random Walks for Ranking and Link Prediction in Networks, KR: 10-2017-0131543 (filed on Nov. 10, 2017) Woojeong Jin, Jinhong Jung, and U Kang
Method for Personalized Ranking in Signed Networks, Recording Medium And Device for Performing the Method, KR: 10-2017-0005485 (filed on Jan. 12, 2017)
Jinhong Jung, Woojeong Jin, and U Kang
Pattern Recognition and Machine Learning (Audit), SNU, Spring 2017 Convex Optimization, SNU, Fall 2016 Mining Massive Datasets, Stanford Online, June 2017 Machine Learning (Stanford University), Coursera, May 2016