孙仲 - 北京大学 - 人工智能研究院

个人简介

2020年至今，北京大学，研究员，北大博雅青年学者，国家高层次青年人才 2016 – 2020，米兰理工大学，博士后 2011 – 2016，清华大学，获博士学位 2007 – 2011，南开大学，获学士学位

研究领域

1. 模拟矩阵计算，包括基本矩阵计算单元设计、模拟电路与模拟计算理论，及面向机器学习、科学计算、无线通信等领域的应用； 2. 基于阻变动力学的神经网络模型，包括阻变存储器电路的动力学特性与应用、吸引子网络理论与算法； 3. 新原理阻变器件，包括器件的创新设计与优化、器件的精准写入机制设计等方面，实现高性能器件与阵列的制备

近期论文

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Mannocci, P., Farronato, M., Lepri, N., Cattaneo, L., Glukhov, A., Sun, Z. & Ielmini, D. In-memory computing with emerging memory devices: Status and outlook. APL Mach. Learn. (2023). Zuo, P., Sun, Z. & Huang, R. Extremely-Fast, Energy-Efficient Massive MIMO Precoding with Analog RRAM Matrix Computing. IEEE Trans. Circuits Syst. II, Exp. Brief (2022). Tan, H., Sun, Z. & Zhu, X. Neuro-inspired Sensing and Computing: Novel Materials, Devices, and Systems. Front. Comput. Neurosci. (2023). Luo, Y., Wang, S., Zuo, P., Sun, Z. & Huang, R. Modeling and Mitigating the Interconnect Resistance Issue in Analog RRAM Matrix Computing Circuits. IEEE Trans. Circuits Syst. I: Regul. Pap. (2022). Sun, Z. & Ielmini, D. Invited Tutorial: Analog Matrix Computing with Crosspoint Resistive Memory Arrays. IEEE Trans. Circuits Syst. II, Exp. Brief (2022). Sun, Z. Analog Matrix Computing with Resistive Memory: Circuits and Theory. VLSI-TSA (2022). Wang, S., Sun, Z., Liu, Y., Bao, S., Cai, Y., Ielmini, D. & Huang, R. Optimization Schemes for In-Memory Linear Regression Circuit With Memristor Arrays. IEEE Trans. Circuits Syst. I: Regul. Pap. (2021). Mannocci, P., Pedretti, G., Giannone, E., Melacarne, E., Sun, Z. & Ielmini, D. A Universal, Analog, In-Memory Computing Primitive for Linear Algebra Using Memristors. IEEE Trans. Circuits Syst. I: Regul. Pap. (2021). Pedretti, G., Mannocci, P., Li, C., Sun, Z., Strachan, J. P. & Ielmini, D. Redundancy and Analog Slicing for Precise in-Memory Machine Learning--Part II: Applications and Benchmark. IEEE Transactions on Electron Devices (2021). Pedretti, G., Mannocci, P., Li, C., Sun, Z., Strachan, J. P. & Ielmini, D. Redundancy and Analog Slicing for Precise in-Memory Machine Learning--Part I: Programming Techniques. IEEE Transactions on Electron Devices (2021). Li, H., Wang, S., Zhang, X., Wang, W., Yang, R., Sun, Z., Feng, W., Lin, P., Wang, Z., Sun, L. & Yao, Y. Memristive Crossbar Arrays for Storage and Computing Applications. Advanced Intelligent Systems (2021). Sun, Z. & Huang, R. Time Complexity of In Memory Matrix-Vector Multiplication. IEEE Trans. Circuits Syst. II, Exp. Brief (2021). Ielmini, D., Pedretti, G., Mannocci, P. & Sun, Z. Regression and Optimization by Analogue In-memory Computing in Crosspoint Arrays. ECS Meeting Abstracts (2020). Sun, Z., Pedretti, G., Ambrosi, E., Bricalli, A. & Ielmini, D. In-Memory Eigenvector Computation in Time O(1). Advanced Intelligent Systems (2020). Sun, Z., Ambrosi, E., Pedretti, G., Bricalli, A. & Ielmini, D. In-Memory PageRank Accelerator With a Cross-Point Array of Resistive Memories. IEEE Transactions on Electron Devices 67, 1466-1470 (2020). Sun, Z., Pedretti, G., Ambrosi, E., Bricalli, A. & Ielmini, D. In-Memory PageRank Using a Crosspoint Array of Resistive Switching Memory (RRAM) Devices. 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) (2020). Sun, Z., Pedretti, G., Bricalli, A. & Ielmini, D. One-step regression and classification with cross-point resistive memory arrays. Science Advances 6, eaay2378 (2020). Sun, Z., et al. Time Complexity of In-Memory Solution of Linear Systems. IEEE Transactions on Electron Devices 67, 2945-2951 (2020). Sun, Z., Pedretti, G. & Ielmini, D. Fast Solution of Linear Systems with Analog Resistive Switching Memory (RRAM). 2019 IEEE International Conference on Rebooting Computing (ICRC) (2019). Sun, Z., et al. In-memory solution of linear systems with crosspoint arrays without iterations. 2019 Device Research Conference (DRC) (2019). Sun, Z., et al. Solving matrix equations in one step with cross-point resistive arrays. Proceedings of the National Academy of Sciences 116, 4123-4128 (2019). Wang, W., et al. Surface diffusion-limited lifetime of silver and copper nanofilaments in resistive switching devices. Nature Communications 10, 81 (2019). Sun, Z., Ambrosi, E., Bricalli, A. & Ielmini, D. Logic Computing with Stateful Neural Networks of Resistive Switches. Advanced Materials 30, 1802554 (2018). Sun, Z., et al. Built-In-Homojunction-Dominated Intrinsically Rectifying-Resistive Switching in NiO Nanodots for Selection-Device-Free Memory Application. Advanced Electronic Materials 3, 1600361 (2017). Zhao, D., et al. Magnetoresistance Behavior of Conducting Filaments in Resistive-Switching NiO with Different Resistance States. ACS Applied Materials & Interfaces 9, 10835-10846 (2017). Sun, Z., et al. Deterministic Role of Concentration Surplus of Cation Vacancy Over Anion Vacancy in Bipolar Memristive NiO. ACS Applied Materials & Interfaces 8, 11583-11591 (2016). Miao, P., et al. Ferroelectricity and Self-Polarization in Ultrathin Relaxor Ferroelectric Films. Scientific Reports 6, 19965 (2015). Jiang, X., et al. Characteristics of different types of filaments in resistive switching memories investigated by complex impedance spectroscopy. Applied Physics Letters 102, 253507 (2013).