High effective-resolution built-in jitter characterization with quantization noise shaping. - Leyi Yin; Yongtae Kim 001; Peng Li 001 (DAC, 2011)

An ultra-low voltage digitally controlled low-dropout regulator with digital background calibration. - Yongtae Kim 001; Peng Li 001 (ISQED, 2012)

A digital neuromorphic VLSI architecture with memristor crossbar synaptic array for machine learning. - Yongtae Kim 001; Yong Zhang 049; Peng Li 001 (SoCC, 2012)

An energy efficient approximate adder with carry skip for error resilient neuromorphic VLSI systems. - Yongtae Kim 001; Yong Zhang 049; Peng Li 001 (ICCAD, 2013)

A 0.38 V near/sub-VT digitally controlled low-dropout regulator with enhanced power supply noise rejection in 90 nm CMOS process. - Yongtae Kim 001; Peng Li 001 (IET Circuits Devices Syst., 2013)

A Reconfigurable Digital Neuromorphic Processor with Memristive Synaptic Crossbar for Cognitive Computing. - Yongtae Kim 001; Yong Zhang 049; Peng Li 001 (ACM J. Emerg. Technol. Comput. Syst., 2015)

Energy Efficient Approximate Arithmetic for Error Resilient Neuromorphic Computing. - Yongtae Kim 001; Yong Zhang 049; Peng Li 001 (IEEE Trans. Very Large Scale Integr. Syst., 2015)

A Parallel Digital VLSI Architecture for Integrated Support Vector Machine Training and Classification. - Qian Wang 003; Peng Li 001; Yongtae Kim 001 (IEEE Trans. Very Large Scale Integr. Syst., 2015)

Neuromorphic Processors with Memristive Synapses: Synaptic Interface and Architectural Exploration. - Qian Wang 003; Yongtae Kim 001; Peng Li 001 (ACM J. Emerg. Technol. Comput. Syst., 2016)

Bit-Shuffle Coding for Flicker Mitigation in Visible Light Communication. - Youngsun Han; Yongtae Kim 001; Byung Wook Kim (IEEE Access, 2019)

A 9 Gb/s/ch Transceiver With Reference-Less Data-Embedded Pseudo-Differential Clock Signaling for Graphics Memory Interfaces. - Junyoung Song; Yongtae Kim 001; Chulwoo Kim (IEEE Trans. Circuits Syst. II Express Briefs, 2019)

Design of a Low-Cost Approximate Adder with a Zero Truncation. - Jungwon Lee; Hyoju Seo; Yerin Kim; Yongtae Kim 001 (ISOCC, 2020)

An Energy-Efficient Imprecise Adder with a Lower-part Constant Approximation. - Hyoju Seo; Yoon Seok Yang; Yongtae Kim 001 (ISOCC, 2020)

Recent Trend of Neuromorphic Computing Hardware: Intel's Neuromorphic System Perspective. - Yoon Seok Yang; Yongtae Kim 001 (ISOCC, 2020)

A Novel ReRAM-Based Architecture of Field Sequential Color Driver for High-Resolution LCoS Displays. - Youngsun Han; Dongmin Kim; Yongtae Kim 001 (IEEE Access, 2020)

Approximate adder design with simplified lower-part approximation. - Jungwon Lee; Hyoju Seo; Yerin Kim; Yongtae Kim 001 (IEICE Electron. Express, 2020)

Training and Inference using Approximate Floating-Point Arithmetic for Energy Efficient Spiking Neural Network Processors. - Myeongjin Kwak; Jungwon Lee; Hyoju Seo; Mingyu Sung; Yongtae Kim 001 (ICEIC, 2021)

Precision Exploration of Floating-Point Arithmetic for Spiking Neural Networks. - Myeongjin Kwak; Hyoju Seo; Yongtae Kim 001 (ISOCC, 2021)

Design of an Accuracy Enhanced Imprecise Adder with Half Adder-based Approximation. - Hyoju Seo; Jungwon Lee; Hyelin Seok; Yongtae Kim 001 (ISOCC, 2021)

Resource-Optimized Design of Bit-Shuffle Block Coding for MIMO-VLC. - Youngsun Han; Sanghyeon Lee; Byung Wook Kim; Yongtae Kim 001 (IEEE Access, 2021)

A Novel Approximate Adder Design Using Error Reduced Carry Prediction and Constant Truncation. - Jungwon Lee; Hyoju Seo; Hyelin Seok; Yongtae Kim 001 (IEEE Access, 2021)

Low-Power Cross-Layer Error Management Using MIMO-LDPC Iterative Decoding for Video Processing. - Yoon Seok Yang; Yongtae Kim 001 (IEEE Access, 2021)

Do Not Forget: Exploiting Stability-Plasticity Dilemma to Expedite Unsupervised SNN Training for Neuromorphic Processors. - Myeongjin Kwak; Yongtae Kim 001 (ICCD, 2022)

An Accurate and Efficient Stochastic Computing Adder Exploiting Bit Shuffle Control Scheme. - Donghui Lee; Junhyuk Baik; Yongtae Kim 001 (ISOCC, 2022)

A Novel Efficient Approximate Adder Design using Single Input Pair based Computation. - Hyelin Seok; Hyoju Seo; Jungwon Lee; Yongtae Kim 001 (ISOCC, 2022)

Segmented Match-Line and Charge-Sharing Based Low-Cost TCAM. - Minseob Shim; Junwon Jeong; Junyoung Song; Yongtae Kim 001; Woong Choi (IEEE Trans. Circuits Syst. II Express Briefs, 2022)

Towards Quantized Stochastic Computing by Leveraging Reduced Precision Binary Numbers through Bit Truncation. - Donghui Lee; Yongtae Kim 001 (ICCD, 2023)

A Smith-Waterman Hardware Accelerator Design using Sliding Window for Genomic Sequence Alignment. - Junhyuk Baik; Donghui Lee; Yongtae Kim 001 (ISOCC, 2023)

Enhancing Stochastic Computing using a Novel Hybrid Random Number Generator Integrating LFSR and Halton Sequence. - Donghui Lee; Junhyuk Baik; Yongtae Kim 001 (ISOCC, 2023)

Computation Exactness Exploration of Exact Quantum Adders in NISQ. - Hyoju Seo; Seokhyeon Lee; Yongtae Kim 001 (ISOCC, 2023)

TorchAxf: Enabling Rapid Simulation of Approximate DNN Models Using GPU-Based Floating-Point Computing Framework. - Myeongjin Kwak; Jeonggeun Kim; Yongtae Kim 001 (MASCOTS, 2023)

A Low Latency Approximate Adder Design Based on Dual Sub-Adders With Error Recovery. - Hyoju Seo; Yongtae Kim 001 (IEEE Trans. Emerg. Top. Comput., 2023)

Design of an Efficient Parallel Random Number Generator Using a Single LFSR for Stochastic Computing. - Donghui Lee; Hyoju Seo; Yongtae Kim 001 (ICAIIC, 2024)

Comparative Analysis of Quantum Adder Circuits in Computation Accuracy on Noisy Quantum Computers. - Sungyoun Hwang; Hyoju Seo; Yongtae Kim 001 (ISOCC, 2024)

Design of a Low-Cost Stochastic Computing-based Median Filter for Digital Image Processing. - Donghui Lee; Yongtae Kim 001 (ISOCC, 2024)

Enabling Quantum Computer Simulation under Minimal Precision Floating-Point using Irrational Value Decomposition. - Hyoju Seo; Yongtae Kim 001 (MASCOTS, 2024)

A comprehensive exploration of approximate DNN models with a novel floating-point simulation framework. - Myeongjin Kwak; Jeonggeun Kim; Yongtae Kim 001 (Perform. Evaluation, 2024)

Online Electric Vehicle Charging Strategy in Residential Areas With Limited Power Supply. - Dong-Hee Yoon; Hyoju Seo; Jungwon Lee; Yongtae Kim 001 (IEEE Trans. Smart Grid, 2024)

Accuracy Performance Analysis of Quantized DNN Models Using Approximate 4-2 Compressor Based Multipliers. - Seokhyeon Lee; Jeonggeun Kim; Yongtae Kim 001 (ICAIIC, 2025)

QQ: Is 2-bit Enough? Exploiting Quantization to Enhance Computation and Memory Efficiency in Quantum Simulation. - Hyoju Seo; Seokhyeon Lee; Yongtae Kim 001 (ICCAD, 2025)

Can Less Accurate Be More Accurate? Surpassing Exact Multiplier with Approximate Design on NISQ Quantum Computers. - Sungyoun Hwang; Hyoju Seo; Yongtae Kim 001 (SAC, 2025)

Exploiting Omega Network and Inexact Accumulative Parallel Counter to Enhance Energy Efficiency in Stochastic Computing. - Donghui Lee; Yongtae Kim 001 (SAC, 2025)

Hardware-Efficient Quantized Stochastic Computing With Reduced Precision Stochastic Number Generator and LFSR-Based Counter. - Donghui Lee; Yongtae Kim 001 (Int. J. Circuit Theory Appl., 2025)

Design of a Hardware-Efficient Approximate 4-2 Compressor for Multiplications in Image Processing. - Sungyoun Hwang; Kon-Woo Kwon; Yongtae Kim 001 (IEEE Embed. Syst. Lett., 2025)

quEStab: Towards Scalable Quantum Circuit Simulation on Multi-GPU using an Extended Stabilizer Formalism. - Hyunjoon Shin; Seokhyeon Lee; Myeongjin Kwak; Yongtae Kim 001 (ICS, 2026)

A Stride-based Sequence Aligner with Boundary-Aware Multi-Seed Traceback for Genomic DNA Sequence Analysis. - Donghui Lee; Inuk Jung; Yongtae Kim 001 (SAC, 2026)

Design of Approximate Floating-Point Arithmetic Units Using Hardware-Efficient Rounding Schemes. - Myeongjin Kwak; Seokhyeon Lee; Yongtae Kim 001 (IEEE Embed. Syst. Lett., 2026)