Mingu Kang

Mingu Kang is an Associate Professor in the Electrical and Computer Engineering Department at the University of California, San Diego. His research focuses on digital and analog Very Large-Scale Integration (VLSI) circuit, architecture, and system for machine learning and signal processing algorithms based on emerging computing paradigms. The VVIP (Vertically-integrated VLSI Information Processing) Lab, led by Professor Kang, aims to develop energy- and latency-efficient VLSI hardware for machine learning and signal processing algorithms. He joined UCSD in 2020 as an Assistant Professor and previously worked at IBM Thomas J. Watson Research Center and Samsung Electronics.

Mingu Kang is an Assistant Professor at UC San Diego, specializing in Machine learning, Circuit, and Architecture. Their research focuses on developing energy-efficient and high-throughput VLSI architectures for machine learning applications, particularly in-memory computing and AI accelerators. Kang's work explores the integration of memory and computation to enhance performance and reduce power consumption in deep neural networks and pattern recognition systems. They have contributed to the design of in-memory inference processors, robust classifiers, and hybrid AI chips that support both training and inference. Their research emphasizes the use of SRAM and MRAM technologies for scalable and efficient AI systems.