Contact Information Address : Dept. of Creative IT Convergence Engineering, POSTECH, Pohang, South Korea
Education Ph.D. 2016.2 – POSTECH, South Korea
Dept. of Creative IT Engineering B.S. 2012.2 – 2016.2 POSTECH, South Korea Dept. of Creative IT Engineering (Magna Cum Laude) 2015.4 – 2015.9 Technische Universität Berlin, Germany (exchange student)
Industry Experience Intern 2015.12 ~ 2016.03 Internship, Winter, 2015-2016 - Efficient graph partitioning on a distributed graph engine Oracle Labs, Belmont, CA, USA - Performance analysis and tuning of graph analytics and graph queries in large-scale graphs on a distributed graph engine
Scholarship Scholarship 2016.08 2016 Google Anita Borg Scholars APAC - Kim, H., So, B., Han, W., and Lee, H., "Natural language to SQL: Where are we today?," In 46th Int'l Conf. on Very Large Data Bases (VLDB) / Proc. the VLDB Endowment (PVLDB), Vol. 13, No. 10, August 2020 (ISSN: 2150-8097). - Kim, H., Lee, J., Bhowmick, S., Han, W., Lee, J., Ko, S., and Jarrah, M., "DualSim: Parallel Subgraph Enumeration in a Massive Graph on a Single Machine," In Proc. 42nd Int'l conf. on Management of Data, ACM SIGMOD, San Francisco, USA, June 2016.
Selected Projects- Development of disk-based gradient descendant method (course project) In this project, I have developed a disk-based, gradient descendant algorithm on top of TurboGraph, which can be used for disk-based recommendation. During this project, I have analyzed important parts of source codes of TurboGraph. - Development of algorithms for a distributed, disk-based graph database engine In this project, I have proposed and developed a graph partitioning algorithm and a distributed and disk-based triangle counting algorithm on top of TurboGraph++. - Development of a deep learning-based method for transforming large-scale unstructured data to structured data In this project, I have proposed and developed a technique for transforming unstructured web data (e.g., job posting) to structured data by using CNN and RNN.
Areas of Interest Natural Language Processing, Database Query Processing, Deep Learning, Graph Databases, Graph Data Analysis, Big Data Processing
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