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Seung-Hwan Lim

Seung-Hwan Lim

Research Scientist

Contact

LIMS1@ORNL.GOV

Bio

I am a computer scientist who works on machine learning on discrete structures like graph and sequences. 

Google scholar entry:

Publications

May 2025

GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism

Conference Paper
December 2024

SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks

Conference Paper
April 2024

Scaling neural simulations in STACS

Journal: Neuromorphic Computing and Engineering
April 2024

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

Conference Paper
January 2024

Efficient graph representation framework for chemical molecule similarity tasks

Conference Paper

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Computing and Computational Sciences Directorate
Computer Science and Mathematics Division
Mathematics in Computation Section
Discrete Algorithms Group

Related News

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Translational symmetries constrain how phonons interact in layered magnets

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Adaptive Single Parameter Total Variation Regularization for Derivative Estimation

Research Highlight

Versatile Feature Learning with Graph Convolutions and Graph Structures

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ORNL technologies receive six R&D 100 Awards
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