担任职务：

北京大学心理与认知科学学院教授

北京大学定量生物学中心教授

研究方向：

计算神经科学与类脑计算

研究兴趣：

通过和认知科学家、神经科学家、信息科学家等合作，用数理方法和计算机仿真来构建神经系统加工信息的计算模型，阐明大脑处理信息的一般性原理，并在此基础上发展类脑的人工智能算法

工作经历：

1995-1997：香港科技大学物理系 博士后

1997-1998：比利时林堡大学物理系 博士后

1998-2000：日本理化学所-脑科学所 博士后

2000-2003：英国谢菲尔德大学计算机系 讲师

2003-2008：英国萨斯克斯大学信息工程系 高级讲师

2008-2011：中国科学院神经科学研究所 研究员

2011-2017：北京师范大学“认知神经科学与学习”国家重点实验室 教授

2018-2020：北京大学信息科学技术学院 教授

2021-至今：北京大学心理与认知科学学院 教授

代表性文章：

• Xiaohan Lin#, Xiaolong Zou#, Zilong Ji, Tiejun Huang;Si Wu*, Yuanyuan Mi*, A brain-inspired computational model for spatio-temporal information processing,Neural Networks, 2021, 143:74-87.

• Xingsi Dong#, Tianhao Chu#, Tiejun Huang, Zilong Ji*, Si Wu*. Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks. NeurIPS 2021.

• W. Zhang, H. Wang, A. Chen, Y. Gu, T. S. Lee, KYM Wong*, S. Wu*(2019). Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation. eLife 8: e43753.

• X. Liu, X. Zou, Z. Ji, G. Tian, Y. Mi, T. Huang, KYM Wong, S. Wu*(2019). Push-pull feedback implements hierarchical information retrieval efficiently.NeurIPS, 2019.

• W.H. Zhang,&S. Wu, B. Doiron, T.S. Lee. A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits.&NeurIPS, 2019.

• Xiaolan Wang, C.C. Alan Fung, Shaobo Guan,Si Wu*, Michael E. Goldberg, Mingsha Zhang* (2016). Perisaccadic Receptive Field Expansion in the Lateral Intraparietal Area. Neuron, 90(2): 400–409.

• W. Zhang, A. Chen, M. Rasch* andS. Wu* (2016). Decentralized multi-sensory information integration in neural systems.The Journal of Neuroscience, 36(2):532-547.

• W. Zhang, H. Wang, KYM Wong, S. Wu*(2016). “Concurrent” and “Opposite” Neurons: Sisters for Multisensory Integration and Segregation.NeurIPS, 2016.

• Wu, S*, Wong, KYM., Fung, CCA., Mi, Y., and Zhang, W. (2016). Continuous attractor neural networks: candidate of a canonical model for neural information representation.F1000 Invited Review, 66(16), 209-226.

• Y. Yan, M. Rasch, M. Chen, X. Xiang, M. Huang,S. Wu and W. Li (2014). Perceptual training continuously refines neuronal population codes in primary cortex.Nature Neuroscience17: 1380–1387. doi:10.1038/nn.3805.

• Y. Mi, C. C. Alan Fung, K. Y. Michael Wong,S.Wu*(2014).Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural NetworksNeurIPS, 2014.

• Y. Mi , X. Liao , X. Huang , L. Zhang , W. Gu, G. Hu* and S. Wu*(2013). Long-Period Rhythmic Synchronous Firing in a Scale-Free Network.Proc. Natl. Acad. Sci. USA&110:E4931-4936.

• L. Xiao, M. Zhang, D. Xing, P-J. Liang and S. Wu* (2013). Shift of Encoding Strategy in Retinal Luminance Adaptation: from Firing Rate to Neural Correlation.Journal of Neurophysiology 110:1793-1803. doi:10.1152/jn.00221.2013.

• Tsodyks, M. and Wu, S* (2013). Short-term synaptic plasticity. Scholarpedia, 8(10):3153.

• C. C. Fung, K. Y. Michael Wong, H. Wang and S. Wu* (2012). Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy and Mobility.Neural Computation 24 (5): 1147-1185, 2012.

• C. C.Fung, K.Y.Michael Wong and S. Wu* (2010). A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks. Neural Computation, v.22, p.752-792.

• C. C. Fung, K. Y. Michael Wong, H. Wang and S.Wu* (2010). Attractor Dynamics with Synaptic Depression. NeurIPS 2010.

• D. Chen, S. Li, Z. Kourtzi and S. Wu* (2010). Behavior-constrained support vector machines for fMRI data analysis. IEEE Trans. Neural Networks. v. 21, 1680-1685.

• C. C.Fung, K.Y.Michael Wong and S. Wu* (2008). Tracking Changing Stimuli in Continuous Attractor Neural Networks. NeurIPS 2008.

• S. Wu& and S. Amari (2005). Computing with Continuous Attractors: Stability and On-Line Aspects. Neural Computation, v.17, 2215-2239.

• S. Wu and K. Y. Michael Wong and B. Li. (2002). A Dynamic Call Admission Policy for Precision QoS Guarantee Using Stochastic Control for Mobile Wireless Networks. IEEE/ACM Transactions on Networking, v.10, p.257-271.

• S. Wu, S. Amari and H. Nakahara. (2002). Population Coding and Decoding in a Neural Field: A Computational Study. Neural Computation, v14, no.5, p.999-1026.

• S. Wu and S. Amari. (2002). Neural Implementation of Bayesian Inference in Population Codes. NeurIPS 2002.

• S. Wu, H. Nakahaara, N. Murata and S. Amari. (2000). Population Decoding Based on an Unfaithful Model. ;NeurIPS 2000.

• S. Amari and S. Wu (1999). Improving Support Vector Machine Classifiers by Modifying Kernel Functions. Neural Networks, v.12, p.783-789, 1999.

获奖情况：

无

其它成果：
无

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