MING
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Ming Wang

Ming Wang (王明), Associate Professor, Frontier Institute of Chip and System, Fudan University, China. His research interest includes resistive switching devices (RRAM), memristors, neuromorphic computing devices and systems, flexible and stretchable sensors, and intelligent perception 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 2021 at Nanyang Technological University, Singapore. From 2021, Dr. Wang started his independent scientific career as a Tenure-Track Principal Investigator (Associate Professor) in Fudan University.

Official  /  Google Scholar  /  Researchgate  /  ORCiD

Open Position Announcement:

Graduate students and postdoctoral candidates are welcome to join the group. If interested, please contact Dr. WANG (wang_ming@fudan.edu.cn) with your CV.

Research

  • In-sensor & near-sensor computing for intelligent systems

    • Advanced intelligent systems such as wearable devices, prosthetic hands and robotics have numerous sensory nodes to capture surrounding stimuli. Conventionally, sensory nodes are interfaced with front-end electronics that convert and transmit sensory signals to external computers or the cloud for data processing, resulting in long latency and high energy consumption. Near-sensor or in-sensor computing, where computation tasks are performed near or within sensors, has been recently proposed to alleviate this issue by shortening the data transmission distance between sensors and computing units.

  • Novel devices & algorithms for neuromorphic computing

    • Conventional computing platforms based on the von Neumann architecture are facing challenges in the big-data era, due to their separated memory and processing units. Neuromorphic computing emulating a biological brain at different levels offers a promising way to overcome the memory wall, which requires to exploit brain-inspired principles in designing novel devices, algorithms, and architectures.

  • Resistive switching devices for non-volatile memory

    • Reversible resistive switching devices (memristors) induced by an electric field in dielectrics shows a promising application in future information storage and processing. However, memristors suffer from several challenges, such as unclear resistive switching mechanisms, high operation current, state instability, excessive cycle-to-cycle and device-to-device variations, and sneak current for array integration.

    Publications

    1. T. Wang†, M. Wang(共同一作)†, J. Wang, L. Yang, X. Ren, G. Song, S. Chen, Y. Yuan, R. Liu, L. Pan, Z. Li, W. R. Leow, Y. Luo, S. Ji, Z. Cui, K. He, F. Zhang, F. Lv, Y. Tian, K. Cai, B. Yang, J. Niu, H. Zou, S. Liu, G. Xu, X. Fan, B. Hu*, X. J. Loh, L. Wang, and X. Chen*. A chemically mediated artificial neuron. Nature Electronics (2022). | Link

    2. M. Wang, J. Tu, Z. Huang, T. Wang, Z. Liu, F. Zhang, W. Li, K. He, L. Pan, X. Zhang, X. Feng, Q. Liu, M. Liu, and X. Chen*. Tactile near-sensor analogue computing for ultrafast responsive artificial skin. Advanced Materials (2022). | Link

    3. X. Liu, J. Cao, J. Qiu, X. Zhang, M. Wang*(通讯作者), and Q. Liu. Flexible and stretchable memristive arrays for in-memory computing. Frontiers in Nanotechnology 3, 821687 (2022). | Link

    4. M. Zhu, S. Ji, Y. Luo, F. Zhang, Z. Liu, C. Wang, Z. Lv, Y. Jiang, M. Wang, Z. Cui, G. Li, L. Jiang*, Z. Liu*, and X. Chen*. A mechanically interlocking strategy based on conductive microbridges for stretchable electronics. Advanced Materials 34, 2101339 (2022). | Link

    5. J. Zhu, X. Zhang*, R. Wang, M. Wang, P. Chen, L. Cheng, Z. Wu, Y. Wang, Q. Liu*, and M. Liu. A Heterogeneously Integrated Spiking Neuron Array for Multimode‐Fused Perception and Object Classification. Advanced Materials 2200481 (2022). | Link

    6. W. Kong, Y. Yang, Y. Wang, H. Cheng, P. Yan, L. Huang, J. Ning, F. Zeng, X. Cai*, and M. Wang*(通讯作者). An ultra-low hysteresis, self-healing and stretchable conductor based on dynamic disulfide covalent adaptable networks. Journal of Materials Chemistry A 10, 2012–2020 (2022). | Link

    7. J. Cao, X. Zhang, H. Cheng, J. Qiu, X. Liu, M. Wang*(通讯作者), and Q. Liu. Emerging dynamic memristors for neuromorphic reservoir computing. Nanoscale 14, 289-298 (2022). | Link

    8. J. Yu, Z. Liu, M. Wang, C. Wang, G. Chen, Z. Cui, T. Wang, H. Yang, X. Wang, and X. Chen*. Strain‐Enabled Phase Transition of Periodic Metasurfaces. Advanced Materials 34, 2102560 (2022). | Link

    9. T. Wang†, Z. Cui†, Y. Liu*, D. Lu, M. Wang, C. Wan, W. R. Leow, C. Wang, L. Pan, X. Cao, Y. Huang, Z. Liu, A. I. Y. Tok, and X. Chen*. Mechanically Durable Memristor Arrays Based on a Discrete Structure Design. Advanced Materials 34, 2106212 (2022). | Link

      Before Fudan (2021)

    10. M. Wang, T. Wang, Y. Luo, K. He, L. Pan, Z. Li, Z. Cui, Z. Liu, J. Tu, and X. Chen*. Fusing stretchable sensing technology with machine learning for human–machine interfaces. Advanced Functional Materials 31, 2008807 (2021). | Link

    11. W. Li, N. Matsuhisa, Z. Liu, M. Wang, Y. Luo, P. Cai, G. Chen, F. Zhang, C. Li, Z. Liu, Z. Lv, W. Zhang, and X. Chen*. An on-demand plant-based actuator created using conformable electrodes. Nature Electronics 4, 134-142 (2021). | Link

    12. M. Wang, Y. Luo, T. Wang, C. Wan, L. Pan, S. Pan, K. He, A. Neo, and X. Chen*. Artificial skin perception. Advanced Materials 33, 2003014 (2021). | Link

    13. M. Wang†, Z. Yan†, T. Wang, P. Cai, S. Gao, Y. Zeng, C. Wan, H. Wang, L. Pan, J. Yu, S. Pan, K. He, J. Lu, and X. Chen*. Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors. Nature Electronics 3, 563-570 (2020). | Link

    14. C. Wan†, P. Cai†, X. Guo, M. Wang, N. Matsuhisa, L. Yang, Z. Lv, Y. Luo, X. J. Loh, and X. Chen*. An artificial sensory neuron with visual-haptic fusion. Nature communications 11, 4602 (2020). | Link

    15. M. Wang*(通讯作者), K. Guo, and H. Cheng. Stretchable HfO2-Based Resistive Switching Memory Using the Wavy Structured Design. IEEE Electron Device Letters 41, 1118-1121 (2020). | Link

    16. P. Cai, C. Wan, L. Pan, N. Matsuhisa, K. He, Z. Cui, W. Zhang, C. Li, J. Wang, J. Yu, M. Wang, Y. Jiang, G. Chen, and X. Chen*. Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures. Nature communications 11, 2183 (2020). | Link

    17. L. Pan, F. Wang, Y. Cheng, W. R. Leow, Y.-W. Zhang, M. Wang, P.g Cai, B. Ji, D. Li*, and X. Chen*. A supertough electro-tendon based on spider silk composites. Nature communications 11, 1332 (2020). | Link

    18. T. Wang†, M. Wang(共同一作)†, L. Yang, Z. Li, X. J. Loh, and X. Chen*. Cyber–physiochemical interfaces. Advanced Materials 32, 1905522 (2020). | Link

    19. M. Wang, T. Wang, P. Cai, and X. Chen*. Nanomaterials discovery and design through machine learning. Small Methods 3, 1900025 (2019). | Link

    20. W. Wang, M. Wang, E. Ambrosi, A. Bricalli, M. Laudato, Z. Sun, X. Chen*, and D. Ielmini*. Surface diffusion-limited lifetime of silver and copper nanofilaments in resistive switching devices. Nature communications 10, 81 (2019). | Link

    21. M. Wang, W. Wang, W. R. Leow, C. Wan, G. Chen, Y. Zeng, J. Yu, Y. Liu, P. Cai, H. Wang, D. Ielmini*, and X. Chen*. Enhancing the matrix addressing of flexible sensory arrays by a highly nonlinear threshold switch. Advanced Materials 30, 1802516 (2018). | Link

    22. M. Wang†, J. Zhou†, Y. Yang, S. Gaba, M. Liu, and W. D Lu*. Conduction mechanism of a TaOx-based selector and its application in crossbar memory arrays. Nanoscale 7, 4964-4970 (2015). | Link

    23. M. Wang†, C. Bi†, L. Li, S. Long, Q. Liu, H. Lv, N. Lu, P. Sun, and M. Liu*. Thermoelectric Seebeck effect in oxide-based resistive switching memory. Nature communications 5, 4598 (2014). | Link

    24. M. Wang, H. Lv, Q. Liu, Y. Li, Z. Xu, S. Long, H. Xie, K. Zhang, X. Liu, H. Sun, X. Yang, and M. Liu*. Investigation of one-dimensional thickness scaling on Cu/HfOx/ Pt resistive switching device performance. IEEE Electron Device Letters 33, 1556-1558 (2012). | Link

    News

  • Grants 2021.12, Dr. Wang 获国家重点研发计划项目资助，主持。

  • Grants 2021.12, Dr. Wang 获国家优秀青年项目（海外）资助，主持。

  • Rewards 2021.08, Dr. Wang 获复旦大学新工科人才基金资助 。

  • Grants 2021.08, Dr. Wang 获国家自然科学基金（青年）项目资助，主持。

  • Rewards 2021.02, Dr. Wang 获上海海外高层次人才计划。

  • Grants 2021.01, Dr. Wang 获上海脑中心“求索杰出青年”研究组长项目资助，主持。

    • Contact

    MING WANG office:

    Frontier Institute of Chip and System

    Room 3014, Cross Building No.1, Riverside campus, Fudan University

    2005, Songhu Road, Yangpu District, Shanghai, China

    地址：上海市杨浦区淞沪路2005号复旦大学江湾校区交叉1号楼B3014室

    Email：wang_ming@fudan.edu.cn

    Phone：021-31242701

    Welcome to jion Ming Wang's group!