教育经历 1999.9 - 2003.7：北京大学，微电子学与固体电子学专业，本科毕业，获理学学士学位 2004.9 - 2009.7：北京大学，微电子学与固体电子学专业，研究生毕业，获理学博士学位，导师：韩汝琦先生 进修经历 2006.8 - 2007.8：于瑞典隆德大学进修或培训 工作经历 2009.6 - 2010.11：中国科学院微电子研究所，博士后（已出站），合作导师：刘明院士 2010.12 - 2015.8：大阪大学产业科学研究所，特任研究员（聘期已结束），合作导师：川合知二先生、谷口正輝教授、筒井真楠准教授

类脑计算与器件

An Ultrafast Sparse Solution Solver made by HfWOx/VOy Threshold Tunable Neurons.[M].IEDM,2023, Computational event-driven vision sensors for in-sensor spiking neural networks.[J].Nature Electronics,2023, Reconfigurable two-WSe2-transistor synaptic cell for reinforcement learning.Advanced Materials,2022, Reconfigurable Synaptic and Neuronal Functions in a V/VOx/HfWOx/Pt Memristor for Nonpolar Spiking Convolutional Neural Network.[J].Advanced Functional Materials,2022, Graphene–ferroelectric transistors as complementary synapses for supervised learning in spiking neural network.[J].NPJ 2D Materials & Applications,2019,31 Threshold Switching Memristor-based Stochastic Neuron for Probabilistic Computing.[J].Materials Horizons,2021,619-629 Nanochannel-Based Transport in an Interfacial Memristor Can Emulate the Analog Weight Modulation of Synapses.[J].Nano Letters,2019,4279-4286 Complementary Graphene-Ferroelectric Transistors (C-GFTs) as Synapses with Modulatable Plasticity for Supervised Learning.[C].2019 IEEE International Electron Devices Meeting,2019, Complementary Memtransistors based Multilayer Neural Networks for Online Supervised Learning through (anti-) Spiking-Timing Dependent Plasticity.[J].IEEE Transactions on Neural Networks & Learning Systems,2021, Solid-state nanopore systems: From materials to applications.[J].NPG Asia Materials,2021,48