曹 磊

时间:2020-12-14浏览:0设置

曹磊,博士,讲师,研究生导师。人工智能专业主任。2016年直博毕业于同济大学,取得计算机软件与理论专业博士学位,2013年于德国图宾根大学进行研究访问。先后主持国家自然科学基金1项、上海市教育研究基金1项,参与国家自然科学基金中外交流合作项目、面上基金项目、青年基金项目、横向课题项目近20余项,发表SCI论文近30篇,获得授权发明专利1项。研究方向为人工智能,大数据,脑机接口,医学影像信号分析,数据挖掘,自然语言处理等。曾于百度上海研发中心工作近2年,参与百度移动云事业部用户画像、智能推荐、贷款逾期风控等项目。联系方式:lcao@shmtu.edu.cn

个人经历
2005-2009 同济大学       电子与信息工程学院信息安全专业           学士学位 
2009-2016 同济大学       电子与信息工程学院计算机软件与理论        博士学位
2013    德国图宾根大学 医学心理学及行为神经生物学研究所             访问学者

 

 


项目工作经历
科研项目
1 国家自然科学基金青年科学基金,62102242,基于中风上肢康复的镜像脑机接口关键技术研究,2022.01-2024.12科研项目
2 上海市教育科学研究项目,C2022152,在线学习中学生注意力评估及提升方法研究,2022.01-2024.12
3 国家自然科学基金青年科学基金,62103258,基于DSmT的多粒度动态融合推理方法及应用研究,2022.01-2024.12
4 国家自然科学基金青年科学基金,61806122,大数据环境下基于进化多任务机制的多目标优化算法研究,2019.01-2021.12
5 国家自然科学基金青年科学基金,61701297,面向船舶监控的目标基高效视频编码关键技术,2018.01-2020.12
6 国家自然科学基金国际(地区)合作交流项目,61550110252Simultaneous EEG and fNIRS based brain computer interface (BCI) for communication in Amyotrophic Lateral Sclerosis (ALS) patient 2016.01-2017.12
7 国家自然科学基金面上项目,61173116,基于动作链及镜像神经系统的人类动作行为理解的认知计算研究,2012.01-2015.12
8 国家自然科学基金青年科学基金,61105122,多模式融合的脑机接口的机理与方法研究,201201-2014.12
9 德国基金委员会项目“基于CLIS病人的脑机接口系统研究”
 
工作经历
百度上海研发中心,AI研发工程师,生活服务场景的大数据分析与挖掘:主要负责用户行为信息挖掘(包括常驻点特征及其属性、作息时间、兴趣爱好、app使用特点)算法设计与实现、结果分析与评估。
论文成果
Cao, L., Chen, S., Jia, J., Fan, C., Wang, H. and Xu, Z.. An Inter- and Intra-Subject Transfer Calibration Scheme for Improving Feedback Performance of Sensorimotor Rhythm-Based BCI Rehabilitation. Frontiers in Neuroscience, 2021.Wang, Z., Zhang, Y., Shi, H., Cao, L.*, Yan, C. and Xu, G.. Recurrent spiking neural network with dynamic presynaptic currents based on backpropagation. International Journal of Intelligent Systems. 2022, 37(3), 2242-2265.

Cao, L., Liu, T., Fan, C., Wang, H., and Wang, Z.. Alertness-based Subject-dependent and Subject-independent filter optimization for Improving Classification Efficiency of SSVEP Detection. Technology and Health Care, 2020.173-180.

Cao, L., Fan, C., Wang, H., and Zhang, T.: A Novel Combination Model of CNN and LSTM for Upper Limb Evaluation Using Kinect-based System, IEEE ACCESS, 2019

Cao, L., Lie, T., Hou, L., Wang, Z., Li, J., and Wang, H.: A Novel Real-Time Multi-Phase BCI Speller Based on Sliding Control Paradigm of SSVEP, IEEE ACCESS, 2018

Wang Z., Cao, L.; Zhang Z., Short time Fourier transformation and deep neural networks for motor imagery brain computer interface recognition , Concurrency and Computation-Practice & Experience, 2018.1.11, 30(23)

Cao, L., Xia, B. et al., A Synchronous Motor Imagery Based Neural Physiological Paradigm for Brain Computer Interface Speller , Frontiers in Human Neuroscience, 2017.05.29, 11: 0~274

Xia B., Cao, L., et al., A binary motor imagery tasks based brain-computer interface for two-dimensional movement control, JOURNAL OF NEURAL ENGINEERING , 2017.12, 14(6)

Xia B., Cao, L., et al., A binary motor imagery tasks based brain-computer interface for two-dimensional movement control, JOURNAL OF NEURAL ENGINEERING , 2017.12, 14(6)

Cao, L., Li, J., Ji, H., and Jiang, C.: A hybrid brain computer interface system based on the neurophysiological protocol and brain-actuated switch for wheelchair control, J NEUROSCI METH, 2014, 229, pp. 33-43

Cao, L., Zhengyu, J., Li, J., Jian, R., and Jiang, C.: Sequence Detection Analysis Based on Canonical Correlation for Steady-state Visual Evoked Potential Brain Computer Interfaces, J NEUROSCI METH, 2015

Cao, L., Li, J., Xu, Y., Zhu, H., and Jiang, C.: A Hybrid Vigilance Monitoring Study for Mental Fatigue and Its Neural Activities, COGN COMPUT, 2015, pp. 1-9

Li, J., Ji, H., Cao, L., Zang, D., Gu, R., Xia, B., and Wu, Q.: Evaluation and application of a hybrid brain computer interface for real wheelchair parallel control with multi-degree of freedom, INT J NEURAL SYST, 2014, 24, (04), pp. 1450014

Xia, B., Maysam, O., Veser, S., Cao, L., Li, J., Jia, J., Xie, H., and Birbaumer, N.: A combination strategy based braincomputer interface for two-dimensional movement control, J NEURAL ENG, 2015, 12, (4), pp. 46021

Ji, H., Li, J., Lu, R., Gu, R., Cao, L., and Gong, X.: EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme, Computational Intelligence and Neuroscience, 2015, 501, pp. 506742

Li, J., Ji, H., Cao, L., Gu, R., Xia, B., and Huang, Y.: Wheelchair Control Based on Multimodal Brain-Computer Interfaces, International journal of neural system, pp. 434-441




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