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自动化研究所人才库

  • 姓名: 余山
  • 性别: 男
  • 职称: 研究员
  • 电子邮件: shan.yu@ia.ac.cn
    简  历:
  • 余山,博士,研究员,现任模式识别国家重点实验室副主任。

    教育经历:

    2000年毕业于中国科学技术大学生物系,2005年于中国科学技术大学获生物学博士学位。2005年至2014年分别在德国马克斯普朗克脑研究所及美国国立精神卫生研究所从事博士后研究。

    工作经历

    20149月加入中科院自动化研究所,任模式识别国家重点实验室以及脑网络组研究中心研究员,博士生导师。研究得到自然科学基金面上项目、科技部重点研发计划、中科院先导专项的支持。

    主要研究方向及内容:

    1 信息处理的脑网络机制

    大脑皮层实现感觉、运动、认知等各种功能依赖于巨量相互作用的神经元构成的复杂网络结构。理解这一庞大而复杂的神经网络如何对信息进行解码、编码和处理是理解大脑工作原理的一个重要方面。这涉及神经元相互作用的结构,神经群体编码,神经网络内部及不同网络之间的通讯方式,网络状态的调控等基本问题。我们使用多道微电极阵列在完成各种行为任务(比如工作记忆)的动物模型上记录神经网络的活动,并结合复杂网络、信息论、统计力学等理论框架对实验数据进行分析,研究神经网络信息处理的基本规律。

    2 类脑计算与类脑智能

      以深度神经网络为代表的专用人工智能近年来得到了迅速的发展,在一些专门的感知领域已经逐渐接近人类的水平。但是对比人类展现的通用智能,特别是对于多任务、动态复杂环境的的高适应性等核心能力,现有人工智能还有很大的差距。我们从人类认知能力受到启发,并借鉴真实大脑中信息处理的基本规律,设计新型算法及网络结构,使得人工智能系统的效率更高、能力更强,从而逐步逼近类人的通用智能。

    3 脑机接口

       以生物大脑为基础的人的智能与以计算机为基础的人工智能具有各自不同的优势和局限,未来一个重要的发展方向是把这两种智能形式结合起来,形成更高级的融合智能。要实现这一目的,需要有新一代的脑机接口技术,能够收集海量的脑活动数据,进行准确、实时的解码,并对神经网络的活动进行精确调控,从而在生物脑与AI之间建立极高带宽的双向信息传送通道。我们结合动物模型和人的实验,并与其他实验室合作,正在开发测试这样的脑机接口系统。

       已发表论文:

    1. Guyue Hu; Bo Cui; Yuan He; Shan Yu; Progressive Relation Learning for Group Activity Recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020

    2. Zeng, Guanxiong#; Chen, Yang#; Cui, Bo; Yu, Shan; Continual learning of context-dependent processing in neural networks, Nature Machine Intelligence, 2019, 1(8): 364.  

    3. Zeng, Guanxiong; Huang, Xuhui; Jiang, Tianzi; Yu, Shan; Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks, Neural Networks, 2019, 118: 140-147.

    4. Zhang, Jinpeng; Zhang, Jinming; Hu, Guyue; Chen, Yang; Yu, Shan; Scalenet: A Convolutional Network to Extract Multi-Scale and Fine-Grained Visual Features, IEEE Access, 2019, 7: 147560.  

    5. Guyue Hu; Xuhui Huang; Tianzi Jiang; Shan Yu; Multi-scale Expressions of One Optimal State Regulated by Dopamine in the Prefrontal Cortex, Frontiers in Physiology, 2019, 10: 113.   

    6. Hu, Guyue; Cui, Bo; Yu, Shan; Skeleton-based action recognition with synchronous local and non-local spatio-temporal learning and frequency attention, IEEE International Conference on Multimedia and Expo (ICME) 2019

    7. Niu, Weikun; Huang, Xuhui; Xu, Kaibin; Jiang, Tianzi; Yu, Shan; Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks, Neuroscience, 2019, 412: 190-206.  

    8. Hu, Guyue; Cui, Bo; Yu, Shan; Joint Learning in the Spatio-temporal and Frequency Domains for Skeleton-Based Action Recognition, IEEE Transactions on Multimedia, 2019

    9. Miller, Stephanie R.; Yu, Shan; Plenz, Dietmar; The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ–oscillations, Scientific Reports, 2019, 9(1): 1.

    10. Wang Zhengchun; Yu Shan; Fu Yu; Tzvetanov Tzvetomir; Zhou Yifeng; Aging Potentiates Lateral but Not Local Inhibition of Orientation Processing in Primary Visual Cortex, Frontiers in Aging Neuroscience, 2018, 10: 0-14. 

    11. Jinpeng Zhang; Jinming Zhang; Shan Yu; Hot Anchors: A Heuristic Anchors Sampling Method in RCNN-Based Object Detection, Sensors, 2018, 18(10): 3415.

    12. Song Ming; Yang Yi; He Jianghong; Yang Zhengyi; Yu Shan; Xie Qiuyou; Xia Xiaoyu; Dang Yuanyuan; Zhang Qiang; Wu Xinhuai; Cui Yue; Hou Bing; Yu Ronghao; Xu Ruxiang; Jiang Tianzi; Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics, eLife, 2018, 7: 0-e36173.

    13. Huang, Xuhui; Xu, Kaibin; Chu, Congying; Jiang, Tianzi; Yu, Shan; Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain, Journal of Neuroscience, 2017, 37(43): 10481-10497.   

    14.Yu, Shan#; Ribeiro, Tiago L#; Meisel, Christian; Chou, Samantha; Mitz, Andrew; Saunders, Richard; Plenz, Dietmar; Maintained avalanche dynamics during task-induced changes of neuronal activity in nonhuman primates., Elife, 2017, 6.   

    15.Yu, Shan; New challenge for bionics--brain-inspired computing., Zoological Research, 2016, 37(5): 261-262.   

    16.余山; 从脑网络到人工智能——类脑计算的机遇与挑战, 科技导报, 2016, (07): 75-77.   

    17. Yu, Shan; Yang, Hongdian; Shriki, Oren; Plenz, Dietmar; Critical exponents, universality class, and thermodynamic temperature of the brain, WileyVCH Verlag GmbH & Co. KGaA, 2014. 

    18. Yu, Shan#; Klaus, Andreas#; Yang, Hongdian; Plenz, Dietmar; Scale-invariant neuronal avalanche dynamics and the cut-off in size distributions., PLoS One, 2014, 9(6): e99761-e99761.  

    19. Yu, Shan#; Yang, Hongdian#; Shriki, Oren; Plenz, Dietmar; Universal organization of resting brain activity at the thermodynamic critical point., Frontiers in Systems Neuroscience, 2013, 7: 42-42.  

    20. Folias, Stefanos E; Yu, Shan; Snyder, Abigail; Nikolic, Danko; Rubin, Jonathan E; Synchronisation hubs in the visual cortex may arise from strong rhythmic inhibition during gamma oscillations., European Journal of Neuroscience, 2013, 38(6): 2864-2883.   

    21. Fu, Yu#; Yu, Shan#; Ma, Yuanye; Wang, Yongchang; Zhou, Yifeng; Functional degradation of the primary visual cortex during early senescence in rhesus monkeys., Cerebral Cortex, 2013, 23(12): 2923-2931.   

    22. Havenith, Martha N.; Yu, Shan; Biederlack, Julia; Chen, Nan-Hui; Singer, Wolf; Nikolic, Danko; Synchrony Makes Neurons Fire in Sequence, and Stimulus Properties Determine Who Is Ahead, Journal of Neuroscience, 2011, 31(23): 8570-8584.   

    23. Klaus, Andreas; Yu, Shan; Plenz, Dietmar; Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches, Plos One, 2011, 6(5).   

    24. Yu, Shan; Nikolic, Danko; Quantum mechanics needs no consciousness, Annalen Der Physik, 2011, 523(11): 931-938.  

    25. Shew, Woodrow L.; Yang, Hongdian; Yu, Shan; Roy, Rajarshi; Plenz, Dietmar; Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches, Journal of Neuroscience, 2011, 31(1): 55-63.   

    26. Yu, Shan; Yang, Hongdian; Nakahara, Hiroyuki; Santos, Gustavo S; Nikolic, Danko; Plenz, Dietmar; Higher-order interactions characterized in cortical activity., Journal of Neuroscience, 2011, 31(48): 17514-17526.   

    27. Jurjut, Ovidiu F.; Nikolic, Danko; Singer, Wolf; Yu, Shan; Havenith, Martha N.; Muresan, Raul C.; Timescales of Multineuronal Activity Patterns Reflect Temporal Structure of Visual Stimuli, Plos One, 2011, 6(2).   

    28. Hahn, Gerald; Petermann, Thomas; Havenith, Martha N.; Yu, Shan; Singer, Wolf; Plenz, Dietmar; Nikolic, Danko; Neuronal Avalanches in Spontaneous Activity In Vivo, Journal of Neurophysiology, 2010, 104(6): 3312-3322.   

    29. Havenith, Martha N.; Zemmar, Ajmal; Yu, Shan; Baudrexel, Simon M.; Singer, Wolf; Nikolic, Danko; Measuring sub-millisecond delays in spiking activity with millisecond time-bins, Neuroscience Letters, 2009, 450(3): 296-300.  

    30. Yu, Shan; Huang, Debin; Singer, Wolf; Nikolic, Danko; A Small World of Neuronal Synchrony, Cerebral Cortex, 2008, 18(12): 2891-2901.   

    31. Yu, Shan; Wang, Yongchang; Li, Xiangrui; Zhou, Yifeng; Leventhal, AG; Functional degradation of extrastriate visual cortex in senescent rhesus monkeys, Neuroscience, 2006, 140(3): 1023-1029.    (期刊论文)

    32. Yu, S; Wang, XS; Fu, Y; Zhang, J; Ma, YY; Wang, YC; Zhou, YF; Effects of age on latency and variability of visual response in monkeys, Chinese Science Bulletin, 2005, 50(11): 1163-1165.  

    33. Liu, N; Yu, S; Zhou, YF; Cai, JX; Ma, YY; Age-related effects of bromocriptine on sensory gating in rhesus monkeys, Neuroreport, 2005, 16(6): 603-606.   

    34. Yu, S#; Liu, N#; Zeng, T; Tian, SH; Chen, NH; Zhou, YF; Ma, YY; Age-related effects of bilateral frontal eye fields lesions on rapid eye movements during REM sleep in rhesus monkeys, Neuroscience Letters, 2004, 366(1): 58-62. 

     

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