Byungchul Tak, PhD
Associate Professor
School of Computer Science and Engineering
Department of Data Convergence Computing
Kyungpook National University, Daegu, Republic of Korea
Email: bctak (at) knu.ac.kr
Embedded Files
I am currently a faculty member at Kyungpook National University (KNU), Republic of Korea. My research interests are broadly in Distributed systems, Operating systems, Cloud computing, and Services computing. Prior to joining KNU, I was a computer scientist at IBM TJ Watson Research Center. While at IBM, I contributed to building enterprise-level cloud solutions for IBM business. One of my work was in building the automated container scanning for policy-defined compliance rules. This has been incorporated into the IBM Bluemix container cloud offerings. In another work, I have built solutions for improving the efficiency of IBM TSS (Technical Support Service) operations. My research area of interest broadly includes Distributed Systems, Operating Systems, Cloud Computing, Services Computing, Storage and Large-scale System Data Analysis. My current research topics of focus are:
• Log Analytics: In this work, I try to find ways to uncover hidden information in the large volume of system/application logs to quickly fix the system problems.
• Container Cloud Security: My goal is to quantify how secure the containers are. To achieve this, I seek out to collect information from Internet such as CVE and exploint codes, analyze them and translate them into the security score for various known security container runtimes. I am also building a data processing pipeline that enables us to perform cloud security analytics.
• Problem Determination via Causal System Event Monitoring: I also work on monitoring libc library calls and system calls to understand the causality of distributed applications.
Research Interests
• Log analytics, log-based anamaly detection, root cause analysis
• Container security, Security measurement and quantification
• Cloud Computing, Cloud Management
• Operating System, Virtualization
• Distributed System's Resource, Performance Management
My previous work involves developing an accurate resource accounting framework for the shared services in the cloud computing environment. Today's clouds provide many services such as key-value store and relational database services (and many others). These are shared by many user-instantiated VMs and internal nodes. It is also common that one such service builds upon some other services. Therefore, the shared service infrastructure is composed of a large number of nodes in a complex structure. For managing these infrastructures, knowing the resource consumption by individual user nodes or entities are important for many purposes such as load relocation, replication decisions as well as charging. However, due to internal s/w structures of these services, it is difficult and inaccurate to account resource consumption through traditional statistical methods. I am investigating techniques to account resource usage at a fine-grained level to increase the accuracy of resource accounting.
Another work I have looked into is about determining the performance of user application if it were to be deployed in the cloud. This problem is important for making decisions about which cloud service to use in what ways. One challenge is that it is prohibitive to actually install the entire application to the cloud to test how the performance comes out to be. The complexity of application may be very high taking days or weeks to install correctly, and huge data may have to be migrated to the cloud incurring significant cost. In addition to this, this task of performance estimation may need to be carried out periodically to dynamically adjust the cloud-based deployment to a better cloud. I am currently developing a technique that does not require an actual installation of the application to the cloud and yet can provide accurate performance estimation.
Education
• 2006-2012 PhD, Pennsylvania State University – University Park
• 2001-2003 MS, Korea Advanced Institute of Science and Technology (KAIST)
• 1993-2000 BS, Yonsei University (1996.4-1998.6 Military service)
Employment
• 2017-present Kyungpook National University, Daegu, Republic of Korea
• 2012-2017 Research Staff Member at IBM TJ Watson Research Center, Yorktown Heights, NY, USA
• 2008, 2009, 2010 Summer – IBM Summer internship at IBM TJ Watson Research Center
• 2004-2006 ETRI, Daejun, Republic of Korea
• 2003-2004 DigitalAria, co., Republic of Korea
Awards
• AAAI 2025 Workshop on Preparing Good Data for Generative AI (Good-data'25) Best Paper Award - Feb, 2025
• CCGrid 2023 Best Research Poster Award - May, 2023.
• KIISE Outstanding paper award 2021 (한국정보과학회 컴퓨터시스템 소사이어티우수논문상)
• ICWS 2018 Best paper award - June, 2018
• Next Generation Computing Spring Conference 2nd Best Paper Award (차세대컴퓨팅춘계학회 우수상) – May, 2018
• IBM Outstanding Technical Achievement Award (OTAA) – Mar, 2016
• IBM A-level Achievement Award – Nov, 2015
• IBM Research Division Award – Apr, 2015
• IBM 2nd Patent Plateau Award – Jun, 2014
• IBM 1st Patent Plateau Award – Jun, 2013
• IBM PhD Fellowship – Fall of 2010 to 2011
• College of Engineering Fellowship, Pennsylvania State University – 2006 – 2009
• University Graduate Fellowship, Pennsylvania State University – 2006
• Full-time National Scholarship, KAIST Mar. 2001 – Feb. 2003
• High Honor Student awarded to students of academic excellence, Yonsei University 1998
Services
Associate Editor
Journal of Computing Science and Engineering
Program Committee
• VLDB Industrial track 2026
• KDBC 2025
• IEEE CLOUD 2016, 2017, 2023 [Link], 2024 [Link], 2025
• The 20th International Conference on Internet and Web Applications and Services (ICIW) 2025 [Link]
• IEEE International Conference on Big Data and Smart Computing (BigComp) 2025 [Link]
• Korean DataBase Conference (KDBC) 2024
• VLDB Phd Workshop 2024
• SCALABILITY 2024 [Link]
• IEEE World Congress on Services, Congress Program Committee 2024 [Link]
• International Conference on Cloud Computing (CLOUD) 2019, 2020, 2021, 2022, 2023
• ScalCom (IEEE International Conference on Scalable Computing and Communications) 2018, 2019, 2020, 2021, 2023
• IEEE Conference on Cloud Computing for Emerging Markets (CCEM) 2017, 2018, 2019, 2020, 2021, 2022
• The 9th International Workshop on Autonomic Management of high performance Grid and Cloud Computing (AMGCC'21), 2021
• MASCOTS (International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems) 2017, 2018 [Link], 2019 [Link]
• IEEE SC2 (IEEE International Symposium on Cloud and Service Computing) 2018, 2019
• ICFEC (IEEE International Conf. on Fog and Edge Computing) 2018, 2019
• IoT-HPC (Special Session on Internet of Things and HPC), 2018
• IC2E (IEEE International Conf. on Cloud Engineering), Doctoral Symposium, 2018
• ICCCN (International Conference on Computer Communications and Networks, Data Centers and Big Data Computing Track ) 2017
• BDCOM (IEEE Workshop on Big Data for Cloud Operations Management) 2017
• KIPS Fall Conference 2017
Streering Committee
• 2024 SCALABILITY: The First International Conference on Systems Scalability and Expandability, Nov 17~21, 2024, Valencia, Spain. [Link]
Chair
• 2026 DASFAA Demonstration track chair
• 2024 VLDB PhD Workshop Panel Session
• 2024년 정보과학회 컴퓨터시스템 소사이어티 조직위원장
• Session Chair at MASCOTS workshop 2023, Stony Brook, NY, USA.
• Session Chair at IEEE CLOUD 2023, Chicago, IL, USA.
• Session Chair at IEEE ICWS 2023, Chicago, IL, USA.
• 2023년 정보과학회 컴퓨터시스템 소사이어티 세션좌장
• 2022년 정보과학회 컴퓨터시스템 소사이어티 출판담당
• 2021년 KSC 프로그램 위원, Poster세션, Oral세션 좌장
• 2021년 정보과학회 컴퓨터시스템 소사이어티 세션 좌장
• Local Chair at KOCSEA 2014, Yorktown Heights, NY, USA.
• Session Chair at IEEE CLOUD 2014, Anchorage, AK, USA.
Guest Editor
• STVR(Software Testing, Verification and Reliability) Journal Special issue for IEEE Pacific Rim International Symposium on Dependable Computing (PRDC2022)
IEEE Technical Community on Services Computing (TCSVC) Executive Committee
http://tab.computer.org/tcsvc/#2-committee
Editorial Board
• Services Transactions on Cloud Computing (STCC)
• Services Transactions on Internet of Things (STIOT)
Journal Reviewer
• ACM TOIT in 2019, 2025
• Theoretical Computer Science in 2025
• IEEE Internet of Things Journal in 2024
• ACM TOSEM in 2024
• PLOS ONE in 2024
• Journal of Internet of Things in 2024
• Journal of Supercomputing in 2024
• IEEE TPDS in 2018
• IEEE TSC
• IEEE TCC
• IEEE TDSC
• IEEE Access
• Cluster Computing
Google Sites
Report abuse