Young-Kyoon Suh is a professor in the School of Computer Science and Engineering, Kyungpook National University (KNU), Daegu, Korea. He has founded the Laboratory of Database and Big Data Systems at KNU. Prior to KNU, he worked as senior researcher at Korea Institute of Science and Technology Information (KISTI). He holds a Ph.D. degree in Computer Science from University of Arizona, Tucson, AZ, USA. His research interests include database design/systems, ergalics (the science of computing), big data processing, reachability query processing on large graphs, software testing, and provenance-data management. He is a recipient of Best Poster Award of IEEE/ACM CCGrid 2016 and Best Paper Award of EDB 2016. He has published several papers in numerous prestigious conferences and scholarly journals. He has also served as a reviewer at some top-tier venues such as ER, SIGMOD, and ICDE. He is a member of ACM, IEICE, and Sigma XI. [My Calendar]

Research Areas

• Database Design/Systems, Performance Evaluation, HPC
• Science of Databases, Micro-specialization in DBMSes (RA under Prof. Richard T. Snodgrass, dissertation advisor)
• Automated Partitioning Design in Row and Column Stores (Internship at Teradata)
• Flash Memory (Solid-State Drive) DBMS for Transactional Database Applications
• Big Data (Hadoop), Buffer Management Scheme for Large-Scale Graphs, Information Integration, and (Sensor) Data Streams
• Provenance Management for Large-scale Scientific Computing Programs

Biography

• Ph.D., Department of Computer Science, University of Arizona, Tucson, AZ, USA, 2015.

Work Experience

• Assistant Professor, School of Computer Science and Engineering, Kyungpook National University (KNU), Daegu, Korea (current)
• Senior Researcher, Korea Institute of Science and Technology Information (KISTI), Daejeon, Korea
• Teaching Assistant & Research Associate, Department of Computer Science, University of Arizona, Tucson, AZ, USA.
• Research Intern, Teradata Corporation, El Segundo, CA, USA.

Refereed Journal Articles

• Jin Ma, Sik Lee, Kum Won Cho, and Young-Kyoon Suh^*, "A Simulation-Provenance Data Management System for Efficient Job Execution on an Online Computational Science Engineering Platform," Cluster Computing, Vol. ??, No. ?, pp. ??–??, 201?.
• Ki Yong Lee and Young-Kyoon Suh^*, "A Pattern-Based Outlier Region Detection Method for 2-Dimensional Arrays," The Journal of Supercomputing, Vol. ??, No. ?, pp. ??–??, 201?.
• Young-Kyoon Suh^*, Alain Crolotte, and Pekka Kostamaa, "MLPPI Wizard: An Automated Multi-Level Partitioning Tool on Analytical Workloads," KSII Transactions on Information Systems, Vol. 12, No. 4, pp. 1693–1713, 2018.
• Young-Kyoon Suh^*, "SEDONA: A Novel Protocol for Identifying Infrequent, Long-running Daemons on a Linux System," IEICE Transactions on Information Systems, Vol. E101-D, No. 1, pp. 239–243, 2018.
• Ki Yong Lee, Young-Kyoon Suh^*, and Kum Won Cho, "Development of a Simulation Result Management and Prediction System Using Machine Learning Techniques," International Journal of Data Mining and Informatics (IJDMB), Vol. 19, No. 1, pp. 75–96 2017.
• Young-Kyoon Suh^*, Richard T. Snodgrass, and Sabah Currim, "An Empirical Study of Transaction Throughput Thrashing Across Multiple Relational DBMSes," Information Systems (Info. Syst.) 66:119–136, 2017.
• Sabah Currim, Richard T. Snodgrass, Young-Kyoon Suh^*, and Rui Zhang, "DBMS Metrology: Measuring Query Time," ACM Transactions on Database Systems (TODS) 42(1):3:1–42(+8), 2017 (extended version).
• Young-Kyoon Suh^*, Richard T. Snodgrass, John Kececioglu, Peter J. Downey, Robert S. Maier, and Cheng Yi, "EMP: Execution Time Measurement Protocol for Compute-Bound Programs," Software: Practice and Experience (SPE) 47(4): 559-597, 2017.
• Young-Kyoon Suh^*, Bongki Moon, Alon Efrat, Jin-Soo Kim, and Sang-Won Lee, "Memory Efficient and Scalable Address Mapping for Flash Storage Devices," Journal of Systems and Architecture (JSA) 60(4):357–371, 2014.

Refereed Conference Articles

• Ki Yong Lee, YoonJae Shin, YeonJeong Choe, SeonJeong Kim, Young-Kyoon Suh^*, Jeong Hwan Sa, and Kum Won Cho, "Design and Implementation of a Data-Driven Simulation Service System," in Proc. of Emerging Databases - Technologies, Applications, and Theory (EDB'16), Jeju Island, Korea, October 2016 (Best Paper Award).
• Sabah Currim, Richard T. Snodgrass, Young-Kyoon Suh, Rui Zhang, Matthew Wong Johnson, and Cheng Yi, "DBMS Metrology: Measuring Query Time," in Proceedings of the 39th ACM SIGMOD Conference (SIGMOD'13), New York City, NY, USA, pp. 421–432, June 2013 (a/r: 20.4% = 76/372) [poster].
• Young-Kyoon Suh, Ahmad Ghazal, Alain Crolotte, and Pekka Kostamaa, "A New Tool for Multilevel Partitioning in Teradata," in Proceedings of the 21st ACM International Conference on Information and Knowledge Management (CIKM'12), Maui, HI, USA, pp. 2214–2218, October 2012 (a/r: 27.8% = 303/1088).
• Young-Kyoon Suh, Bongki Moon, Alon Efrat, Jin-Soo Kim, and Sang-Won Lee, "Extent Mapping Scheme for Flash Memory Devices," in Proceedings of the 20th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS'12), Arlington, VA, USA, pp. 331–338, August 2012 (a/r: 49/156 = 31.4%).
• Byungsang Kim, Dukyun Nam, Young-Kyoon Suh, June Hawk Lee, Kumwon Cho, and Soonwook Hwang, "Application Parameter Description Scheme for Multiple Job Generation in Problem Solving Environment," in Proceedings of the 4th IEEE International Conference on e-Science and Grid Computing (eScience'07), Bangalore, India, pp. 509–515, December 2007.
• Young-Kyoon Suh, Jin-Hyun Son, and Myoung Ho Kim, "GAGPC: Optimization of Multiple Continuous Queries on Data Streams," in Proceedings of the IASTED International Conference on Database and Applications (DBA'06), Bangalore, India, Innsbruck, Austria, pp. 215–220, February 2006.

Other Publications

• Young-Kyoon Suh and Jin Ma, "SUPERMAN: A Novel System for Storing and Retrieving Scientific-Simulation Provenance for Efficient Job Executions on Computing Clusters," to appear in Proceedings of the 5th International Workshop on Autonomic Management of high performance Grid and Cloud Computing (AMGCC'17), Tucson, AZ, USA, September 2017.
• Young-Kyoon Suh, Hoon Ryu, Hangi Kim, and Kum Won Cho, "EDISON: A Web-Based HPC Simulation Execution Framework for Large-Scale Scientific Computing Software," demonstration [poster] in Proceedings of the 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid'16), Cartagena, Colombia, May 2016 (Best Poster Award).
• Young-Kyoon Suh, Richard T. Snodgrass, and Rui Zhang, "AZDBLab: A Laboratory Information System for Large-Scale Empirical DBMS Studies," demonstration [poster] in Proceedings of the VLDB Endowment, 7(13):1641–1644 (VLDB'14), Hangzhou, China, September 2014.
• WooLam Kang, Dong-Hoon, Choi, Young-Kyoon Suh, and Yoon-Joon Lee, "Integration of Avian Influenza Virus Information Sources for Korea e-Science," demonstration, in Proceedings of the 4th IEEE International Conference on e-Science and Grid Computing (eScience'08), Indianapolis, IN, USA, pp. 372–373, December 2008.

Works-in-Progress

• Sabah Currim, Richard T. Snodgrass, Young-Kyoon Suh^*, and Rui Zhang, "A Causal Model of Query Suboptimality," to be submitted to ACM Transactions on Database System.
• Young-Kyoon Suh, Richard T. Snodgrass, and Rui Zhang, "AZDBLab: A Laboratory Information System for a Large-Scale Empirical DBMS Study," 2015 (extended version).
• Young-Kyoon Suh, Richard T. Snodgrass, John Kececioglu, and Robert Maier, "Characterizing Execution Times of a Computer-bound Program," 2015.

Membership

• ACM, IEICE, Sigma Xi

Technical Skills

• Operating Systems: Linux/Unix, Mac OS X, and Windows.
• Computer Languages: C/(Visual) C++/Java, JSP/Servlet, SQL/PL-SQL, HTML/XML/Ajax, Perl, and Python.
• DBMSes: IBM DB2, JavaDB (Derby), Microsoft SQL Server, MySQL, Oracle, PostgreSQL, and Teradata.
• Code Version Management Systems: CVS, SVN, and GitHub.
• Issue Management Systems: MantisBT and Piazza.
• I/O Performance Measurement: ORION, Hammerora, Spew, and Blktrace.
• Statistical Packages: Gnuplot, Matlab, Matplotlib, Numpy/SciPy, and R.

Miscellaneous

• My DBLP
• My Google Scholar
• Journal Rankings (SCI(E) List as of 11/26/2014)
• Google Scholar Conference and Journal Ranking on Databases and Information Systems
• Conference Rankings Provided by WikiPedia
• Top CS Conferences by BK21+ Korea
• R1, R2, R3, R4
• DB : SIGMOD, VLDB, ICDE, CIDR, CIKM, ...
• Systems: SOSP, OSDI, USENIX ATC, EuroSys, MSST, NAS, MASCOTS, ASPLOS, SoSE...
• How to Write an Abstract provided by Philip Koopman
• Tips for Writing Technical Papers provided by Jennifer Widom
• Tips for a Good Conference Talk provided by Jennifer Widom
• Advice on Research and Writing
• How to read, write and present papers
• How to Be a Good Graduate Student