Eeeseok Lee
Sungkyunkwan University · Computer Science
About the Lab
Professor Eeeseok Lee's research lab focuses on computational materials science and high-performance computing, with a strong emphasis on understanding ion insertion mechanisms in lithium-ion battery materials through advanced simulation techniques such as grand canonical Monte Carlo and ab initio cluster expansion. The lab also specializes in GPU-accelerated terrain rendering and adaptive visualization algorithms, addressing challenges in real-time processing of massive 3D geospatial data using hierarchical data structures like quadtrees. Additionally, the lab explores intelligent information retrieval systems, particularly adaptive agents for personalized and collaborative search. These diverse research directions reflect a multidisciplinary approach combining materials modeling, computer graphics, and artificial intelligence.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Many Li-ion cathode materials transform via two-phase reactions, which can lead to long-term structural damage and limited cyclability. To elucidate the coupling between favorable solid-solution Li intercalation and the underlying cation ordering, we take the high-voltage spinel, Li x Ni 0.5 Mn 1.5 O 4 (0 ≤ x ≤ 1), as a case example. Through grand canonical Monte Carlo (MC) simulations based on the ab initio cluster expansion model, we show a striking dependence between the solid-solution phase
Massive digital elevation models require a large number of geometric primitives that exceed the throughput of the existing graphics hardware. For the interactive visualization of these datasets, several adaptive reconstruction methods that reduce the number of primitives have been introduced over the decades. Quadtree triangulation, based on subdivision of the terrain into rectangular patches at different resolutions, is the most frequently used terrain reconstruction method. This usually accomp
In terrain visualization, the quadtree is the most frequently used data structure for progressive mesh generation. The quadtree provides an efficient level of detail selection and view frustum culling. However, most applications using quadtrees are performed on the CPU, because the pointer and recursive operation in hierarchical data structure cannot be manipulated in a programmable rendering pipeline. We present a quadtree-based terrain rendering method for GPU (Graphics Processing Unit) execut
Faculty of Life Science Engineering, Youngdong University, Chungbuk 370-701, KoreaReceived November 5, 2002Key Words : Cholinesterase, Inhibition, Boronic acid, BenzothiophenonesSince cholinesterases (ChE) such as acetylcholinesterase(AChE) and butyrylcholinesterase (BuChE) play criticalroles for the neurotransmission, the detailed chemicalmechanism of the ChE-catalyzed reactions are welldocumented.
In general, changes in society or the environment are expected depending on changes in terrain. The faster and more accurately these terrain changes can be observed, the faster and more accurately predictions can be made. Recently, three-dimensional (3D) terrain visualization programs, such as flight simulation, allow for interaction with various datasets to predict ecosystem influences in real time. Elaborate terrain data require a very large capacity. To render these large terrain data, the co
The popularization of computers and the Internet has produced an explosion in the amount of information and makes it difficult to find them. In order to complement the works of Wet agents for autonomously browsing or filtering on behalf of the user, we focus on adaptive agents for providing support at query formulation and information filtering. These adaptive or learning agents make it possible to add a layer of personalization and collaboration between the users and the existing search engines
Research Areas
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