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Ming Wang

Ming Wang (王明), Associate Professor, Frontier Institute of Chip and System, Fudan University. His research interest includes resistive switching devices (RRAM), memristors, neuromorphic computing devices and systems, flexible and stretchable sensors, and intelligent sensing systems. He received his B.S. (2009) and PhD (2015) in electronic science & technology and microelectronics from Jilin University and the University of Chinese Academy of Sciences (UCAS) respectively. From 2013 to 2014, he joined the University of Michigan, Ann Arbor as a visiting student. After his PHD, he joined Huawei Technologies Co., Ltd as an algorithm engineer in 2015, followed by a postdoctoral research fellow position from 2016 to 2020 at Nanyang Technological University, Singapore, and joined in Fudan University in 2021. He is now sponsored by the National Key R&D Program of China and the Overseas High-Level Talent of China.


Flexible neuromorphic devices for near-sensor and in-sensor computing

Ming Wang1,2

1Frontier Institute of Chip and System, State Key Laboratory of Integrated Chips and Systems, Fudan University, China (wang_ming@fudan.edu.cn)

2State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, China

Abstract

With the rapid development of information technology, intelligent sensing systems are advancing towards high speed, high energy efficiency, high integration and miniaturization. Traditional information processing architecture based on separated data collection and data computing units results in the limitations of low computing efficiency and high energy consumption. The integration of advanced neuromorphic computing units with the sensor end has become a mainstream trend for intelligent sensing systems, refers to near-sensor or in-sensor computing. Here, I will introduce my recent works about the implementation of near-sensor and in-sensor computing intelligent systems based on flexible neuromorphic devices.