Experience

• Research Scientist, Rebellions Inc., Korea

  • AI Accelerator & Systems

Feb. 2021 - Current

• Research Intern, IBM T.J. Watson Research Center, USA

  • Mentor: Dongsoo Lee, Manager: Pong-Fei Lu

  • Reduced precision deep neural network training

Jun. 2016 - Sep. 2016

Education

• Pohang University of Science and Technology (POSTECH), Korea

  • Ph.D. in Creative IT Engineering (CiTE)

    • Advisor: Prof. Jae-Joon Kim

Mar. 2015 - Feb. 2021

• • B.S. in Creative IT Engineering (CiTE)

    • Graduated Summa Cum Laude, GPA: 4.08/4.3

Mar. 2012 - Feb. 2015

• State University of New York (SUNY) at Stony Brook, USA

  • Exchange Student

    • GPA: 4.0/4.0

Sep. 2012 - Dec. 2012

• Korea Science Academy (KSA) of KAIST, Korea

Mar. 2009 - Feb. 2012

Research Interests

My research interests range from algorithm development to chip design related to neuromorphic engineering and deep learning. Previous/current research projects in which I played a major role include

• Devising a novel supervised learning method for Spiking Neural Networks considering the unique characteristics of spiking neurons [Neurips2020] (Arxiv Link)

• FPGA- and ASIC-level development and demonstration (link) of Spiking Neural Network acceleration hardware (named as FireFly) [Frontiers2018]

• Developing environments and applications for crossbar-based neuromorphic hardware [ISLPED2018]

• SRAM-based in-memory Binary Neural Network hardware design [VLSI2019]

Publications

• Jinseok Kim, Kyungsu Kim, Jae-Joon Kim, "Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks", Conference on Neural Information Processing Systems (NeurIPS), Dec. 2020, (Arxiv Link)

• Hyungjun Kim, Kyungsu Kim, Jinseok Kim, Jae-Joon Kim, "BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations", 8th International Conference on Learning Representations (ICLR), Apr. 2020.

• Jinseok Kim, Jongeun Koo, Taesu Kim, Yulhwa Kim, Hyungjun Kim, Seunghyun Yoo, Jae-Joon Kim, "Area-Efficient and Variation-Tolerant In-Memory BNN Computing using 6T SRAM Array," Symposium on VLSI Circuits (SOVC), Jun. 2019

• Jongeun Koo, Jinseok Kim, Sungju Ryu, Chulsoo Kim, Jae-Joon Kim, "Area-Efficient Transposable 6T SRAM for Fast Online Learning in Neuromorphic Processors," IEEE Custom Integrated Circuits Conference (CICC), Apr. 2019

• Jinseok Kim, Jongeun Koo, Taesu Kim, and Jae-Joon Kim, "Efficient Synapse Memory Structure for Reconfigurable Digital Neuromorphic Hardware," Frontiers in Neuroscience, Nov. 2018

• Jinseok Kim, Yulhwa Kim, Sungho Kim, and Jae-Joon Kim, "Compact Convolution Mapping on Neuromorphic Hardware using Axonal Delay," IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), Jul. 2018 (nominated for best paper award)

• Hyungjun Kim, Taesu Kim, Jinseok Kim, Jae-Joon Kim, "Deep Neural Network Optimized to Resistive Memory with Nonlinear Current-Voltage Characteristics," ACM Journal on Emerging Technologies in Computing Systems (JETC), Jun. 2018

• Taesu Kim, Hyungjun Kim, Jinseok Kim, and Jae-Joon Kim, "Input Voltage Mapping Optimized for Resistive Memory-Based Deep Neural Network Hardware," IEEE Electron Device Letters, Sep. 2017

Recognition

Scholarships

• NRF (National Research Foundation of Korea) Global Ph.D. Fellowship Program

  • "Reconfigurable Neuromorphic Hardware with On-chip Learning Capability for Deep Spiking Neural Networks"

Jul. 2016 - Dec. 2020

• POSTECH-SUNY Korea IT Consilience Creative Program (ITCCP)

Mar. 2012 - Dec. 2020

Awards

• Silver Prize (2nd place) in 21st Annual Samsung HumanTech Paper Award in Computer Science & Engineering Division

  • "Resistance Drift Tolerant Data Coding for 4-Level-Cell Phase-Change Memory"

Feb. 2015

• The best student of the year in ICT Consilience Creative Program

  • MSIP (Ministry of Science, ICT and Future Planning), Korea

Aug. 2014