About

Her primay focus is on driving business profitability through technologies. She has joined the TV business unit to be directly and voluntarily engaged with real-world products. As a research engineer, rather than a research scientist, her interest lies more in applying AI technologies in practical, real-world settings. 

Before that, she had been a pivotal role in initiating and accelerating the development of LG’s new business cloud platforms. Over the course of 16 years, her technical expertise has encompassed three key areas: (1) cloud and networking platforms, (2) machine learning algorithms, and (3) big data modeling and analysis.

In South Korea, she is the only one from the headquarter of Akamai technologies Inc. (the world-first and world-top content distribution networking company). 

Bio

• Jun 2017 - Current: Principal research enigneer in LG Electronics, Seoul, South Korea

  • Apr 2023 - Current: Principal research engineer at the WebOS Software group, HE (Home Entertainment) division 

  • Mar 2020-Mar 2023: Principal research engineer at the iLab., CTO division

  • Jun 2017 - Feb 2020: Principal research engineer at the Advanced robotics lab. CTO division

• Oct 2015 - Mar 2017: Senior performance engineer in Akamai Technologies, Inc., MA, U.S.A 

• Sep 2007 - Jul 2015: Ph.D. in computer science from the University of Massachusetts Amherst (as a research assistant). 

  • Her advisor is Distinguished Professor Jim Kurose (Please visit my advisor's networking textbook, Computer Networking: A Top-Down Approach!)

  • She also worked with Distinguished Professor Brian Neil Levine and Professor Arun Venkataramani. 

• Jan 2005 - May 2007: Research engineer in LG Electronics Woomyeon R&D center

• Mar 2003 - Feb 2005: M.S. in computer science in KAIST

• Mar 1999 - Feb 2003: B.S. in computer science from Yonsei university

• Mar 1996 - Feb 1999: Myungduk foreign language high school (french class) 

Her interests

Keywords: Cloud platform, Machine learning and deep learning algorithms, Big data, Modeling, Statistical analytics, Performance evaluation, Network protocol and architecture design, CDN (Content Distribution Network), MLOps, DevOps

She has hands-on and leadership experiences in the following areas:

• AI based recommendation system and MLOps (2023-Current). This work is found at the link.  

• Cloud platform for a joint venture between LG Electronics and SM Entertainment (2021-2022). This work is found at the link.

• MLOps for for video summarization (2020-2021). Buidling a cloud platform that runs a video summarization application in which deep learning algorithms extract representative information.   

• Deep learning researcher in the Robotics field (2017-2020). Dealing with robotics navigation algorithms -- SLAM (Simultaneous Localization and Mapping) and object detection -- and applying deep learning (or reinforcement learning) algorithms,  via timeseries data of diverse sensors (e.g., a cliff sensor, a camera sensor). One of her works appeared in the IEEE ICCE 2020. 

• Data scientist in the CDN (Content Distribution Network) (2015-2017). Dealing with global-scale timeseries data collected from Akamai's world-largest CDN, and performing statistical data analysis, modeling, and capacity planning. Majorly working on the live video streaming architecture

• FIA (Future Internet Architecture) MobilityFirst (2012-2015). Dealing with UMass-campus-wide network data of up to around 7200 users measured for more than 1 year, and performing statistical data analysis, Markov-chain modeling, and machine learning application. This work appeared in the IEEE INFOCOM 2015, and as an unpublished script. 

• Forensics in a P2P (Peer-to-Peer) Network (2010-2012). Dealing with wired/wireless data (collected from more than 10 houses) in the forensics field, applying machine learning methods, and discussing the U.S. law. This  work appeared in the IEEE INFOCOM 2013.

• Anomaly Detection (2008-2010).  Building a probabilistic model to theoretically validate a suggested anomaly detection method . This work appeared as a fast-tracked and invited paper. 

• P2P (Peer-to-Peer) network - BitTorrent (2007-2008). Building and analyzing timeseries BitTorrent-analytics DB (i.e., a log aggregator) in real-time (>1 TB) using around 300 PlanetLab Linux servers. This work briefly presented at the University of Massachusetts Amherst Computer Science System Lunch.

Ph.D. Research

Publications