World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
33
Citations
4194
World Ranking
6117
National Ranking
216

Overview

Jiyong Woo is affiliated with Kyungpook National University in South Korea and works primarily in the field of Engineering, with a focus on Electrical and Electronic Engineering. Their research spans several interrelated subfields, including Cellular and Molecular Neuroscience, Artificial Intelligence, and Computational Theory and Mathematics.

The main topics of Jiyong Woo's work revolve around advanced memory technologies and neural computing, the study of ferroelectric and negative capacitance devices, neuroscience and neural engineering, neural networks and their applications, quantum-dot cellular automata, and machine learning methods such as Extreme Learning Machines.

Jiyong Woo has authored research published in a number of scientific venues, including Advanced Intelligent Systems, Scientific Reports, Science Advances, and ECS Meeting Abstracts. These venues reflect a diverse engagement with interdisciplinary studies in neuromorphic devices and neuroengineering.

  • Advanced Intelligent Systems
  • Scientific Reports
  • Science Advances
  • ECS Meeting Abstracts

Their recent significant publications include:

  • "Recent Advancements in Emerging Neuromorphic Device Technologies" (2020, Advanced Intelligent Systems)
  • "Exploiting defective RRAM array as synapses of HTM spatial pooler with boost-factor adjustment scheme for defect-tolerant neuromorphic systems" (2020, Scientific Reports)
  • "Retention-aware zero-shifting technique for Tiki-Taka algorithm-based analog deep learning accelerator" (2024, Science Advances)
  • "Three-dimensional vertical structural electrochemical random access memory for high-density integrated synapse device" (2023, Scientific Reports)

Frequent collaborators identified in Jiyong Woo's publications include Jong-Pil Im, Seung Eon Moon, Jeong Hun Kim, and Kyungmi Noh. These coauthors have contributed to multiple pieces of research, indicating a collaborative approach within the neuromorphic systems research community.

  • Jong-Pil Im
  • Seung Eon Moon
  • Jeong Hun Kim
  • Kyungmi Noh

The research focus of Jiyong Woo is primarily on advanced memory and neural computing, with an emphasis on the development and application of neuromorphic technologies, addressing challenges such as defect tolerance in resistive RAM arrays and analog deep learning accelerator performance.

Best Publications

  • Improved Synaptic Behavior Under Identical Pulses Using AlO x /HfO 2 Bilayer RRAM Array for Neuromorphic Systems

    Jiyong Woo;Kibong Moon;Jeonghwan Song;Sangheon Lee

  • HfZrO x -Based Ferroelectric Synapse Device With 32 Levels of Conductance States for Neuromorphic Applications

    Seungyeol Oh;Taeho Kim;Myunghoon Kwak;Jeonghwan Song

  • TiO x -Based RRAM Synapse With 64-Levels of Conductance and Symmetric Conductance Change by Adopting a Hybrid Pulse Scheme for Neuromorphic Computing

    Jaesung Park;Myunghoon Kwak;Kibong Moon;Jiyong Woo

  • RRAM-based synapse devices for neuromorphic systems

    K. Moon;S. Lim;J. Park;C. Sung

  • RRAM-based synapse for neuromorphic system with pattern recognition function

    S. Park;H. Kim;M. Choo;J. Noh

  • Threshold Selector With High Selectivity and Steep Slope for Cross-Point Memory Array

    Jeonghwan Song;Jiyong Woo;Amit Prakash;Daeseok Lee

  • High current density and nonlinearity combination of selection device based on TaO(x)/TiO2/TaO(x) structure for one selector-one resistor arrays

    Wootae Lee;Jubong Park;Seonghyun Kim;Jiyong Woo

  • Demonstration of Low Power 3-bit Multilevel Cell Characteristics in a TaO x -Based RRAM by Stack Engineering

    Amit Prakash;Jaesung Park;Jeonghwan Song;Jiyong Woo

  • Resistive Memory-Based Analog Synapse: The Pursuit for Linear and Symmetric Weight Update

    Jiyong Woo;Shimeng Yu

  • Comprehensive scaling study of NbO2 insulator-metal-transition selector for cross point array application

    Euijun Cha;Jaehyuk Park;Jiyong Woo;Daeseok Lee

  • Ultrathin (l10nm) Nb 2 O 5 /NbO 2 hybrid memory with both memory and selector characteristics for high density 3D vertically stackable RRAM applications

    Seonghyun Kim;Xinjun Liu;Jubong Park;Seungjae Jung

  • Linking Conductive Filament Properties and Evolution to Synaptic Behavior of RRAM Devices for Neuromorphic Applications

    Jiyong Woo;Andrea Padovani;Kibong Moon;Myounghun Kwak

  • Optimized Programming Scheme Enabling Linear Potentiation in Filamentary HfO 2 RRAM Synapse for Neuromorphic Systems

    Jiyong Woo;Kibong Moon;Jeonghwan Song;Myounghoon Kwak

  • Nanoscale (∼10nm) 3D vertical ReRAM and NbO 2 threshold selector with TiN electrode

    Euijun Cha;Jiyong Woo;Daeseok Lee;Sangheon Lee

  • Accelerated Publication: Threshold-switching characteristics of a nanothin-NbO2-layer-based Pt/NbO2/Pt stack for use in cross-point-type resistive memories

    Seonghyun Kim;Jubong Park;Jiyong Woo;Chunhum Cho

  • Hardware implementation of associative memory characteristics with analogue-type resistive-switching device.

    Kibong Moon;Sangsu Park;Junwoo Jang;Daeseok Lee

  • Threshold switching behavior of Ag-Si based selector device and hydrogen doping effect on its characteristics

    Jongmyung Yoo;Jiyong Woo;Jeonghwan Song;Hyunsang Hwang

  • Steep Slope Field-Effect Transistors With Ag/TiO 2 -Based Threshold Switching Device

    Jeonghwan Song;Jiyong Woo;Sangheon Lee;Amit Prakash

  • Understanding and Optimization of Pulsed SET Operation in HfO x -Based RRAM Devices for Neuromorphic Computing Applications

    Andrea Padovani;Jiyong Woo;Hyunsang Hwang;Luca Larcher

  • Effect of Nitrogen Doping on Variability of TaOx -RRAM for Low-Power 3-Bit MLC Applications

    Saiful Haque Misha;Nusrat Tamanna;Jiyong Woo;Sangheon Lee

  • Dual functionality of threshold and multilevel resistive switching characteristics in nanoscale HfO2-based RRAM devices for artificial neuron and synapse elements

    Jiyong Woo;Jiyong Woo;Dongwook Lee;Yunmo Koo;Hyunsang Hwang

  • Bidirectional threshold switching in engineered multilayer (Cu2O/Ag:Cu2O/Cu2O) stack for cross-point selector application

    Jeonghwan Song;Amit Prakash;Daeseok Lee;Jiyong Woo

  • Varistor-type bidirectional switch (J MAX >10 7 A/cm 2 , selectivity∼10 4 ) for 3D bipolar resistive memory arrays

    Wootae Lee;Jubong Park;Jungho Shin;Jiyong Woo

Frequent Co-Authors

Hyunsang Hwang
Hyunsang Hwang Pohang University of Science and Technology
Jaesung Park
Jaesung Park Pohang University of Science and Technology
Shimeng Yu
Shimeng Yu Georgia Institute of Technology
Byoung Hun Lee
Byoung Hun Lee Pohang University of Science and Technology
Luca Larcher
Luca Larcher University of Modena and Reggio Emilia
Sanghun Jeon
Sanghun Jeon Korea Advanced Institute of Science and Technology
Takhee Lee
Takhee Lee Seoul National University
Yoshio Nishi
Yoshio Nishi Stanford University
Daniele Ielmini
Daniele Ielmini Polytechnic University of Milan
Kenji Shiraishi
Kenji Shiraishi Nagoya University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For those interested in Electronics and Electrical Engineering, exploring competency-based online colleges can be a smart choice. These programs focus on mastering specific skills and allow students to progress at their own pace, making them ideal for self-motivated learners.

Military spouses and dependents looking to advance their education will find specialized support through online schools for military spouses. These institutions offer flexibility and understanding of unique scheduling needs.

If starting a degree or certificate program more frequently is important, consider online universities with multiple start dates. They provide greater enrollment flexibility, allowing students to begin their studies almost anytime.

For professionals aiming to quickly enhance their qualifications, 6 month certificate programs that pay well offer accelerated pathways into higher-paying roles in engineering and technology fields.

Best Scientists Citing Jiyong Woo

Trending Scientists