个人简历

代表性荣誉
 2020 霍英东教育基金会青年教师基金
 2019 科学探索奖
 2019 北京智源青年科学家
 2019 科学中国人（2018）年度人物特别奖–杰出青年科学家奖
 2019 Wiley Young Researcher Award 2018/2019（中国唯一获奖者）
 2019 北京市科学技术奖二等奖（第四完成人）
 2018 《麻省理工科技评论》中国区35岁以下科技创新35人
 2018 北京大学第十八届青年教师教学基本功比赛理工组二等奖
 2017 求是杰出青年学者奖
研究简介
长期从事类脑计算研究工作，迄今共发表Nature Nanotechnology、Nature Electronics、Nature Communications等期刊和会议论文90余篇，Web of Science引用4400余次，H因子为30，2篇入选ESI热点论文，7篇入选ESI高被引论文，另撰写中英文专著5章，受邀做国际会议邀请报告26次，包含主旨（keynote）报告2次。主持国家杰青、重点研发计划、霍英东教育基金会青年教师基金、北京智源青年科学家等项目，获科学探索奖、求是杰出青年学者奖、Wiley青年研究者奖、《麻省理工科技评论》中国区35岁以下科技创新35人等奖项。Home
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Our research group is dedicated to innovating and developing artificial neuromorphic devices and arrays with ultra-high computing efficiency, ultra-low computing power consumption, high accuracy and large-scale integration. The main research direction is：
1）Through the microscopic characterization of the ion dynamics process to realize the exploration and recognition of the working mechanism of the device；
2）By simulating the working processes of synapses and neurons in the organism, new types of high-precision, low-power artificial neuromorphic device based on ion migration is designed and prepared;
3）Based on resistive memory and new-type neuromorphic devices, the large-scale integration of devices is realized by using the array structure to realize artificial neural networks and related logic applications.
Microscopic characterization of ion kinetic processes
An in-depth understanding of device microdynamics is crucial to the development of artificial neuromorphic devices and their arrays represented by memristors. This research group systematically and deeply conducted the processes of oxygen ion migration in transition metal oxide memristors, silver ion migration based on cation migration devices, and lithium ion migration in synaptic transistors based on two-dimensional layered semiconductor materials. Through the high-resolution transmission electron microscope (HR-TEM), scanning electron microscope (SEM), conductive scanning probe microscope (CAFM) and other characterization methods, the ion migration process in the memristor is intuitively and deeply displayed, and a variety of artificial The working mechanism of the demeanor device has played a guiding role in device design and array integration.
Artificial neuromorphic device based on ion migration
Traditional neuromorphic devices usually only attempt to simulate biological characteristics in electrical behavior. This research group designed the synaptic transistors and Hetero-synapse devices that can accurately simulate biological synapses from micro-dynamic processes to macro-electrical characteristics through detailed research on the working process of biological synapses. In addition to the conventional transition metal oxide material system, this research group has also studied synaptic transistors based on two-dimensional layered semiconductor materials, organic electrolytes, and artificial neural components based on metal-insulator conversion. An ultra-low power consumption of about 30 fJ / spike is achieved experimentally.
Artificial neural network based on neuromorphic device array
Based on the structure of two-terminal memristors and three-terminal heterologous synaptic devices, this research group is committed to achieving array integration with high integration density and ultra-low power consumption. Based on this array structure, efficient logic operations, machine learning problems, etc. can be achieved. This is of great significance for breaking through the \

研究领域

"""""研究领域：类脑计算、智能硬件、忆阻器"

近期论文

Journal Articles
2020
82. Ilia Valov* and Yuchao Yang*, Memristors with alloyed electrodes. Nature Nanotechnology, https://doi.org/10.1038/s41565-020-0702-9, 2020.
81. Yang Zhang, Zhongrui Wang, Jiadi Zhu, Yuchao Yang, Mingyi Rao, Wenhao Song, Ye Zhuo, Xumeng Zhang, Menglin Cui, Linlin Shen, Ru Huang, and J. Joshua Yang*, Brain-inspired computing with memristors: Challenges in devices, circuits and systems. Applied Physics Reviews, 7, 011308, 2020.
80. Jiadi Zhu,# Teng Zhang,# Yuchao Yang,* and Ru Huang,* A Comprehensive Review on Emerging Artificial Neuromorphic Devices. Applied Physics Reviews, 7, 011312, 2020. (Editor's Pick)
79. Yanghao Wang, Liutao Yu, Si Wu, Ru Huang*, and Yuchao Yang*, Memristor Based Biologically Plausible Memory Based on Discrete and Continuous Attractor Networks for Neuromorphic Systems. Advanced Intelligent Systems, 2000001, 2020.
2019
78. Jingxian Li, Yuchao Yang,* Minghui Yin, Xinhao Sun, Lidong Li,* and Ru Huang,* Electrochemical and thermodynamic processes of metal nanoclusters enabled biorealistic synapses and leaky-integrate-and-fire neurons. Materials Horizons, 7, 71-81, 2020. (Front cover)
77. B. Dang, K. Liu, J. Zhu, L. Xu, T. Zhang, C. Cheng, H. Wang, Y. Yang, Y. Hao, and R. Huang, \
现担任Nano Select副主编、《中国科学：信息科学》青年编委、Scientific Reports编委、《Chinese Physics B》客座编辑、《Journal of Semiconductors》客座编辑、中青科协信息与电子专业委员会副秘书长/理事、中青科协提案专门委员会理事、中国电子学会青工委委员。