What's New

  • Apr. 01, 2018 - I will start my Ph.D. in Computer Science Department at Carnegie Mellon University this fall.
  • Dec. 22, 2017 - A research paper, "Fast and Accurate Random Walk with Restart on Dynamic Graphs with Guarantees" is accepted to WWW'18.
  • Dec. 22, 2017 - A research paper, "TPA: Fast, Scalable and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs" is accepted to ICDE'18.

About

Research Interest: Large Scale Graph Mining, Social Network Analysis, Stream Mining and Machine Learning

I am a PhD student majoring in Computer Science at Carnegie Mellon University. Before that, I was a software developer in SAP Labs Korea. I received M.S. in Computer Science, under Prof. Jehee Lee, and B.S. in Electronic Engineering at Seoul National University.

Education

Ph.D Computer Science

Carnegie Mellon University, Pittsburgh, US (Sep. 2018 - Present)

M.S. Computer Science and Engineering

Seoul National University, Seoul, Korea (Sep. 2012 - Aug. 2014)

B.S. Electrical and Computer Engineering

Seoul National University, Seoul, Korea (Mar. 2008 - Feb. 2012)

Hansung Science High school

Seoul, Korea(Mar. 2006 - Feb. 2008)

Work Experiences

Data Mining Lab, Seoul National University

Research Intern (Apr. 2017 - Jun. 2018)

SAP Labs Korea

Software Developer (Sep. 2014 - Mar. 2017)

Movement Research Lab, Seoul National University

Research Intern (Mar. 2012 - Aug. 2012)

Publication

International

  • 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
    (Acceptance Ratio: 14.8%)
    [PDF] [arXiv] [Code] [Homepage]
  • TPA: Fast, Scalable and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs
    Minji Yoon, Jinhong Jung, and U Kang
    IEEE International Conference on Data Engineering (ICDE) 2018, Paris, France
    [PDF] [arXiv] [Code] [Homepage]
  • PMV: Pre-partitioned Generalized Matrix-Vector Multiplication for Scalable Graph Mining
    Chiwan Park, Ha-Myung Park, Minji Yoon, and U Kang
    Preliminary version at arXiv:1709.09099
    [PDF] [arXiv]

Domestic

  • Online Motion Puppetry for Non-human Characters
    Minji Yoon and Jehee Lee
    Korea Computer Graphics Society (KCGS) 2014
    [PDF(Korean)]
  • Crowd simulation based on Motion Patches
    Minji Yoon, Kyunglyul Hyun, and Jehee Lee
    Korean Society for Precision Engineering (KSPE) 2013
    [PDF(Korean)]

Patent

International

  • Fast, Scalable and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs, PCT/KR2017/012962 (18 Nov 2017)
    Minji Yoon, Jinhong Jung, and U Kang
  • Remote authentication, USA: 15/363,102 (29 Nov 2016)
    Minji Yoon and Chulwon Lee
  • Hint-based query routing and session context sharing, USA: 15/362,238 (28 Nov 2016)
    Yongwook Jeong, Minji Yoon, Ian McHardy, Jeff Albion, Abhishek Singhi, Rich Jones, and Chulwon Lee

Projects & Research

Approximate Random Walk with Restart

Data Mining Lab (Advisor: U kang)
Apr. 2017 – Oct. 2017

Proposed an algorithm computing RWR scores approximately. The proposed algorithm outperforms other state-of-the-art methods in terms of speed and memory efficiency while maintaining high accuracy. I contributed as the first author for a paper accepted in ICDE’18.

Random Walk with Restart on Dynamic Graphs

Data Mining Lab (Advisor: U kang)
July 2017 – Aug. 2017

Proposed an algorithm computing RWR efficiently in time-evolving graphs. The proposed algorithm is the first method that guarantees its exactness on RWR scores on dynamic graphs. The proposed algorithm outperforms previous state-of-the-art dynamic RWR methods. I contributed as the first author for a paper accepted in WWW’18.

Generalized Matrix-Vector Multiplication for Scalable Graph Mining

Data Mining Lab (Advisor: U kang)
Apr. 2017 – Oct. 2017

Proposed an algorithm generalizing matrix-vector multiplication on distributed systems. The proposed algorithm achieves superior scalability than previous graph mining methods. I contributed as co-author for a paper submitted to WSDM’18.

Question Answering System

Data Mining Lab (Advisor: U kang)
Apr. 2017 – Oct. 2017

Proposed Question Answering system which retrieves a correct answer for a given question asked in natural language on any topic. Given several answer candidates, re-ranking module in the system ranks the candidates using Neural Tensor Network. This project is supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP).

SAP HANA Active/Active

SAP Labs Korea
June 2016 – Feb. 2017

Active/Active configuration prepares data in memory for read access in an additional ‘hot standby’ SAP HANA database (a.k.a. the secondary SAP HANA database). Customer could operate two SAP HANA databases. This feature is offered from SAP S/4HANA 1610, FPS01 and SAP HANA 2.0, SPS01. I contributed as co-inventor for two US patents (See Patent above).

SAP HANA Capture and Replay

SAP Labs Korea
June 2015 – Apr. 2016

SAP HANA Capture and Replay captures all incoming SQL statements at the session layer of the SAP HANA database and replays it in the new SAP HANA software to ensure the solution still works correctly. It reduces testing challenges by recording workload instead of developing it. SAP HANA Capture and Replay is offered from SAP HANA SPS12.

SAP HANA Session/EAPI layer

SAP Labs Korea
Sep. 2014 – Mar. 2017

Session layer serves as the front-end of SAP HANA database performing thread handling, resource allocation and packet encoding/decoding. EAPI layer is located between Session and SQL layers, and manages connections, statements and transactions which are involved in SQL execution.

Online Motion Puppetry for Non-human Characters

Movement Research Lab (Advisor: Jehee Lee)
Sep. 2013 – Aug. 2014

Manipulating characters’ motion whose body structures and motion patters are different from those of human in real time by human’s motion. I contributed as the first author for a paper submitted to KCGS’14.

Crowd Simulation based on Motion Patches

Movement Research Lab (Advisor: Jehee Lee)
Mar. 2012 – Aug. 2013

Generating a random crowd simulation in real time using motion data with characters and environments that interact with each other. It generates a random crowd simulation of virtual characters interacting with each other in a non-trivial manner using bunch of raw motion data. I contributed as the first author for a paper submitted to KSPE’13.

AWARDS & HONORS

  • National Science & Technology Scholarship, KOSAF (Mar. 2008 - Feb. 2012)
    Full tuition exemptions for 8 semesters.
  • Cum Laude Graduation Honors, Seoul National University (Feb. 2012)

Technicall Skills

Programming Languages

  • C/C++, MATLAB, Python (Advanced) / Java, SQL (Experienced) / HTML (Intermediate)
  • Proficient with linear algebra and TensorFlow