Min-Soo Kim - Biography
Min-Soo Kim is currently an associate professor of Department of Information and Communication Engineering at Daegu Gyeongbuk Institute of Science & Technology (DGIST). He is leading his research group, InfoLab at DGIST. His current research focus is on multidisciplinary research among databases, data mining, bioinformatics, and machine learning.
Professor Kim earned the Ph.D degree from KAIST in 2006 under the supervision of Professor Kyu-Young Whang, who is a KAIST Distinguished Professor, a Fellow of ACM, and a Fellow of IEEE. His major was in the database area. His dissertation was about the n-gram/2L index structure that significantly reduces the size and improves the performance compared with the previous n-gram inverted index, which is the most actively used index structure for information retrieval and search engines. He published the n-gram/2L papers to VLDB 2005, a top conference in the database field and VLDB Journal (2008), the Rank 1 (among 99) journal of the subject category of computer science and information systems. The n-gram/2L technology was also patented in U.S., Germany, Japan, and Korea. In addition to theoretical research, he has participated in many projects, especially the one funded by Korea Science and Engineering Foundation (KOSEF) developing an object-relational DBMS called ODYSSEUS, which is of 450,000 lines in C/C++, and implemented some major features of SQL99. The results of this project were published at the prestigious IEEE ICDE 2005 and 2007 conferences and received the Best Demonstration Award from ICDE 2005.
After the Ph.D degree, Professor Kim has worked with Professor Jiawei Han at UIUC, who is one of the most renowned computer scientists in the field of data mining, as a post-doctoral fellow for two years. He has worked on some of the hottest topics of data mining such as information network analysis and biomedical data mining, and published some results of network analysis about time-evolving clustering for dynamic networks at VLDB 2009, a top conference in the database field. In case of biomedical data mining, in order to do real interdisciplinary research, he has visited two biomedical groups of Washington University in St. Louis, which is known as the top-3 medical school in US, and studied the problem of identifying the type of embryonic stem cells by using DNA microarray data.
After the Post-doctoral fellow program at UIUC, Professor Kim joined a large-scale project of IBM Almaden research center, where is a world-leading research lab in computer science, especially in database management. The project is developing the main-memory based next generation DBMS called “IBM Smart Analytics Optimizer”(ISAO) for IBM's next generation mainframe system. The purpose of ISAO is to boost analytic performance in data warehousing environment. He has been making many contributions to the query engine, especially about data compression, memory management, and performance optimization. He has also participated in the project for the next version of ISAO called BLink Ultra (BLU) as a core member of query engine development.
Through the Ph.D program at KAIST and the Post-doctoral programs at University of Illinois at Urbana-Champaign (UIUC) and IBM Almaden research center, Professor Kim has experienced both theoretical research in academia and product development in industry in a wide range of fields such as database, data mining, and biomedical science. Such a rich experience on various fields is the driving force behind the multidisciplinary research he is aiming.