Seyoung Kim

Associate Professor

Pohang University of Science and Technology

South Korea

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About

Dr. Seyoung Kim is an Associate Professor at Pohang University of Science and Technology in South Korea. His research focuses on advancing memory technologies and neuromorphic systems, as highlighted by his recent publications on analog switching in memristors and electrochemical field effect transistors. Additionally, his work explores multi-bit ECRAM-based systems and innovative strategies for neural network training and computation efficiency.

Articles (18)

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2025

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2021

Collaborators (1)

Sangbum Kim

Associated Professor

Seoul National University

SOUTH KOREA

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Seyoung Kim

Research Interests

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Articles (18)

Analog Switching in Hexagonal Boron Nitride Memristors via Multiple Nano‐Filaments Confinement

A Novel Indium Gallium Zinc Oxide Channel‐Based Electrochemical Field Effect Transistor for Physical Reservoir Computing

Unconventional Multimodal Switching in Single‐Crystalline Nanowire Channel ECRAM

A Multi-Bit ECRAM-Based Analog Neuromorphic System With High-Precision Current Readout Achieving 97.3% Inference Accuracy

Device Specifications for Neural Network Training with Analog Resistive Cross‐Point Arrays Using Tiki‐Taka Algorithms

Channel-Boosted Electrochemical RAM With a-IGZO TFT for Highly Accurate and Energy-Efficient Neural Network Computation

Highly-efficient and scalable TrioN (3N0C) synaptic cell for analog process-in-memory

Accurate Weight Update in an Electrochemical Random‐Access Memory Based Cross‐Point Array Using Channel‐High Half‐Bias Scheme for Deep Learning Accelerator

Exploiting Read Current Noise of TiOx Resistive Memory by Controlling Forming Conditions for Probabilistic Neural Network Hardware

Integrate-and-Fire Neuron With Li-Based Electrochemical Random Access Memory Using Native Linear Current Integration Characteristics

Effect of Stochastic Resonance on Classification Accuracy of Neural Networks Utilizing Inherent Stochasticity in Threshold Voltage of Ovonic Threshold Switching Device

Experimental measurement of ungated channel region conductance in a multi-terminal, metal oxide-based ECRAM

Impact of Operating Temperature on Pattern Recognition Accuracy of Resistive Array-Based Hardware Neural Networks

Excellent Pattern Recognition Accuracy of Neural Networks Using Hybrid Synapses and Complementary Training

Elucidating Ionic Programming Dynamics of Metal-Oxide Electrochemical Memory for Neuromorphic Computing

Impact of electrolyte density on synaptic characteristics of oxygen-based ionic synaptic transistor

Improvement of Synaptic Properties in Oxygen-Based Synaptic Transistors Due to the Accelerated Ion Migration in Sub-Stoichiometric Channels

Neural Network Training Acceleration With RRAM-Based Hybrid Synapses

Collaborators (1)

Sangbum Kim

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