Mingoo Seok

Columbia University

H指数:37

被引数:5,628

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Sensing to Action: Cognitive Processing for Multispectral Sensors

从感知到行动：多光谱传感器的认知处理

IEEE Micro

IF2.9

2026-09-150

An 1.34-TOPS/W, 16-GOPS/mm² Digital In-Memory-Computing-Based AI Microcontroller Unit Supporting On-Chip Model Fine-Tuning for a TinyML Device

基于数字存内计算，支持片上模型微调的TinyML设备AI微控制器单元，其能效达1.34 TOPS/W，面积效率为16 GOPS/mm<sup>2</sup>

IEEE Transactions on Circuits and Systems I-Regular Papers

IF5.2

2026-08-310

PRE

KWS-CIM: A Charge-Domain eDRAM-Based Compute-in-Memory Macro for Ternary DFSMN Keyword Spotting

KWS-CIM：一种基于电荷域eDRAM的存内计算宏用于三值DFSMN关键词识别

IEEE Transactions on Circuits and Systems I-Regular Papers

IF5.2

2026-08-130

PRE

On-the-Fly Memory Decompression in GPU Featuring In-Partition Compressed Block Prefetching and Gzip Decompression for Scientific Computing

GPU中具有分区内压缩块预取和Gzip解压缩功能的科学计算飞行内存解压

IEEE Transactions on Computers

IF3.8

2026-07-010

PRE

GUARD: A Clock and Voltage Glitch Detector With On-Demand Protection

GUARD：一种按需保护的时钟和电压毛刺检测器

IEEE Journal of Solid-State Circuits

IF5.6

2026-06-010

PRE

IGA-SRAM: A Compact SRAM-Based IMC Engine for Binary/Ternary Deep Neural Networks With ADC-Less and Error-Aware Training Algorithm

IGA-SRAM：一种基于SRAM的紧凑型IMC引擎，用于二值/三值深度神经网络，具有无ADC和误差感知训练算法

IEEE Journal on Emerging and Selected Topics in Circuits and Systems

IF3.8

2026-03-270

PRE

A 7.5-μW 35-Keyword End-to-End Keyword Spotting System With Random Augmented On-Chip Training

IEEE Journal of Solid-State Circuits

IF5.6

2026-02-190

PRE

D6CIM: 60.4-TOPS/W All-Digital 6T-SRAM-Based Compute-in-Memory Macro Supporting 1-to-8 b Fixed-Point Arithmetic in a 28-nm CMOS

D6CIM：60.4-TOPS/W全数字6T-SRAM基存内计算宏，支持1至8位定点运算，采用28纳米CMOS工艺

IEEE Transactions on Circuits and Systems I-Regular Papers

IF5.2

2026-01-014

PRE

AACIM: A 2785-TOPS/W, 161-TOP/mm², <1.17%-RMSE, Analog-In Analog-Out Computing-In-Memory Macro in 28 nm

AACIM：一种在28 nm工艺下实现的模拟输入-模拟输出存内计算宏，具有2785-TOPS/W的能效、161-TOP/mm<sup>2</sup>的面积效率以及小于1.17%的均方根误差

IEEE Journal of Solid-State Circuits

IF5.6

2025-10-280

PRE

T-REX: Hardware–Software Co-Optimized Transformer Accelerator With Reduced External Memory Access and Enhanced Hardware Utilization

T-REX：一种硬件-软件协同优化的Transformer加速器，具有减少外部内存访问和增强硬件利用率的特点

IEEE Journal of Solid-State Circuits

IF5.6

2025-09-030

PRE

A 4.2-to-0.5-V, 0.8-μA-0.8-mA, Power-Efficient Three-Level SIMO Buck Converter for a Quad-Voltage RISC-V Microprocessor

IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS

IF3.1

2025-01-010

PRE

iMCU: A 28-nm Digital In-Memory Computing-Based Microcontroller Unit for TinyML

IEEE JOURNAL OF SOLID-STATE CIRCUITS

IF5.6

2024-08-011

PRE

A 394-TOPS/W Matched Filter With Charge-Domain Computing for GPS Signal Acquisition

IEEE JOURNAL OF SOLID-STATE CIRCUITS

IF5.6

2024-01-010

PRE

A Capacitorless External-Clock-Free Fully Synthesizable Digital LDO With Time-Based Load-State Decision and Asynchronous Recovery

IEEE TRANSACTIONS ON POWER ELECTRONICS

IF6.5

2024-01-013

PRE

MACC-SRAM: A Multistep Accumulation Capacitor-Coupling In-Memory Computing SRAM Macro for Deep Convolutional Neural Networks

IEEE Journal of Solid-State Circuits

IF5.6

2023-01-010

PRE

DIMCA: An Area-Efficient Digital In-Memory Computing Macro Featuring Approximate Arithmetic Hardware in 28 nm

IEEE Journal of Solid-State Circuits

IF5.6

2023-01-010

PRE

A 44.2-TOPS/W CNN Processor With Variation-Tolerant Analog Datapath and Variation Compensating Circuit

Seo, J.O.; Seok, M.; Cho, S. 一种具有抗变化模拟数据通路和变化补偿电路的44.2-TOPS/W CNN处理器。IEEE J. Solid-State Circuits 2024, 59, 1603–1611. [Google Scholar] [CrossRef]

IEEE Journal of Solid-State Circuits

IF5.6

2023-01-010

PRE

TICA: Timing Slack Inference and Clock Frequency Adaption Technique for a Deeply Pipelined Near-Threshold-Voltage Bitcoin Mining Core

IEEE Journal of Solid-State Circuits

IF5.6

2023-01-010

PRE

Channel Estimation Using Deep Learning on an FPGA for 5G Millimeter-Wave Communication Systems

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS

IF5.2

2022-02-017

Always-On Sub-Microwatt Spiking Neural Network Based on Spike-Driven Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device

FRONTIERS IN NEUROSCIENCE

IF3.2

2021-07-206

OAAI

Mingoo Seok

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教育背景

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