Jeonghoon LEE Ph.D.
Principal Research Scientist
Jeonghoon LEE Ph.D.
Principal Research Scientist
245 Daehak-ro, Yuseong-gu
Daejeon, 34141
Republic of Korea
Email, Office: +82-42-869-1698
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Principal Research Scientist
Since 2021, I have been responsible for developing XR content authoring technologies and tools allowing Non-experts to create collaborative XR content with multilateral interactions across heterogeneous and multidisciplinary environment. It is a part of the 6 year’s project titled “Development of Untact Immersive Open XR Platform Technologies” by Korea Ministry of Science and ICT, which aims to develop a unified platform for user’s generating multi-modal immersive XR collaboration services.
Since 2021, I have been responsible for developing XR content authoring technologies and tools allowing Non-experts to create collaborative XR content with multilateral interactions across heterogeneous and multidisciplinary environment. It is a part of the 6 year’s project titled “Development of Untact Immersive Open XR Platform Technologies” by Korea Ministry of Science and ICT, which aims to develop a unified platform for user’s generating multi-modal immersive XR collaboration services.
I am interested in the creation of XR content(3D objects, scenes, interactions) using artificial intelligence, data management of these XR contents as digital assets in Metaverse era, and new user interfaces as the next generation research environment infrastructure.
I am interested in the creation of XR content(3D objects, scenes, interactions) using artificial intelligence, data management of these XR contents as digital assets in Metaverse era, and new user interfaces as the next generation research environment infrastructure.
My academic background is based on Computer Science, especially Database; my researches have been focused on data mining and learning with high dimensional data and expands the machine learning task with stationary data into the framework with multi-stream data considering essential aspects of it: large size, time sensitivity, and concept drift for a long time. The final goals are to characterize high dimensional stream data and develop proper methods to analyze them effectively and efficiently by adopting high performance computing and parallel processing techniques.
My academic background is based on Computer Science, especially Database; my researches have been focused on data mining and learning with high dimensional data and expands the machine learning task with stationary data into the framework with multi-stream data considering essential aspects of it: large size, time sensitivity, and concept drift for a long time. The final goals are to characterize high dimensional stream data and develop proper methods to analyze them effectively and efficiently by adopting high performance computing and parallel processing techniques.
Since joining KISTI (Korea Institute of Science and Technology Information), I have been developing data-intensive science research environment based on scientific big data technologies by establishment of Korea-national scientific data governance system and providing the Korean MSIT (Ministry of Science and ICT) with not only technical but also political support for research data management and sharing at national level. I have also been managing networks of researchers and participating in activities of international cooperative networks for data management and sharing and open science like CODATA, WDS(World Data System), RDA(Research Data Alliance), and OECD as the national delegator of CODATA and working member with WG/IGs (National Data Services, Data Publishing) of WDS and RDA.
Since joining KISTI (Korea Institute of Science and Technology Information), I have been developing data-intensive science research environment based on scientific big data technologies by establishment of Korea-national scientific data governance system and providing the Korean MSIT (Ministry of Science and ICT) with not only technical but also political support for research data management and sharing at national level. I have also been managing networks of researchers and participating in activities of international cooperative networks for data management and sharing and open science like CODATA, WDS(World Data System), RDA(Research Data Alliance), and OECD as the national delegator of CODATA and working member with WG/IGs (National Data Services, Data Publishing) of WDS and RDA.
Carrying out these activities, I have realized the importance of interdisciplinary effort in order to face up to the opportunities and challenges of the new type of data revolution and AI as today’s predominant issue for global science world. Realizing intrinsic values of new reality-related data, the immense movement of managing and sharing the data in all digitally transformed areas already begun and I'd like to meet these needs of the age proactively.
Carrying out these activities, I have realized the importance of interdisciplinary effort in order to face up to the opportunities and challenges of the new type of data revolution and AI as today’s predominant issue for global science world. Realizing intrinsic values of new reality-related data, the immense movement of managing and sharing the data in all digitally transformed areas already begun and I'd like to meet these needs of the age proactively.
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