I am a third-year Ph.D. student majoring in Computer Science at Carnegie Mellon University.
My research interests include large-scale data mining, social network analysis, and big data analytics systems. I am fortunate to be advised by Prof. Christos Faloutsos and supported by
I received B.S. in Computer Science and Engineering and B.A. in Economics at Seoul National University. My undergraduate research was advised by Prof. U Kang and Prof. Byung-Gon Chun.
Ph.D. in Computer Science,
•Sep. 2015 - Present
M.S. in Computer Science, •Dec. 2017
B.S. in Computer Science and Engineering,•Aug. 2015
B.A. in Economics (double major) •Aug. 2015
Research Assistant • Aug. 2015 - Present
Machine Learning and Relevance Engineer Intern • May. 2017 - Aug. 2017
Research Intern (Part-time) • Jan. 2015 - Jun. 2015
Research Intern • Jan. 2014 - Aug. 2014
Associate Researcher • Jan. 2011 - Dec. 2013
Kijung Shin, Tina Eliassi-Rad, and Christos Faloutsos
ICDM 2016 [ paper | appendix | longer ver. [J5] | slides | www (code and datasets) | bib ]
Selected as one of the best papers of ICDM 16 and invited for potential publication at the KAIS Journal
Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, and Christos Faloutsos
KDD 2016 [ paper | longer ver. [J3] | code | bib ]
KDD 2016 Best Paper Award [link], CogX 2017 Award for Best Student Paper in AI [link]
Media: NSF [link], WESA [link], TechXplore [link], Stanford Scholar [link], Crain's [link]
Kijung Shin, Jinhong Jung, Lee Sael, and U Kang
SIGMOD 2015 [ paper | longer ver. [J1] | slides | www (code and datasets) | bib ]
Samsung Humantech Paper Award (1st in Computer Science) [link], Taught in courses: UMich (EECS 598), SIGMOD Student Travel Award
NetMiner is an application software for exploratory analysis and visualization of large network data based on SNA (Social Network Analysis). This tool allows researchers to explore their network data visually and interactively, helps them to detect underlying patterns and structures of the network.
[www | wiki | free trial] • Participation: Jan. 2011 - Dec. 2013
Dolphin is a machine learning platform built on top of Apache REEF. Dolphin consists of a BSP-style machine learning framework (dolphin-bsp), a deep learning framework (dolphin-dnn), and a parameter server module (dolphin-ps).
[Github repo] • Participation: Jan. 2015 - Jun. 2015