报告时间：2018年10月29日（周一）9:00
报告地点：东校区信息馆401
报告题目：《Real-worldNeuroimaging: an Intersection of Neuroscience, Neurotechnologies, and MachineLearning》
报告人：钟子平
报告人简介：钟子平，美籍华人，加州大学圣地亚哥分校（UCSD）教授，Swartz计算神经科学中心副主任，UCSD先进神经工程中心副主任，台湾国立交通大学等高校兼职教授，IEEE Fellow。研究方向主攻计算神经科学、脑机接口、机器学习。其建立了应用盲源分离以分解多通道EEG/MEG/ERP和fMRI数据的变革技术，诸多研究成果曾在SCIENCE、PNAS、PROCEEDINGS OF THE IEEE等多家国际顶级期刊发表，发表论文GOOGLE引用次数总和达22700次，H因子高达59。
报告内容简介：The past twenty years havewitnessed remarkable advances in neuroscience and neurotechnologies. However,nearly all the neuroscience research studies were conducted in well-controlledlaboratory settings. It has been argued that fundamental differences betweenlaboratory-based and naturalistic human behavior may exist. It remains unclearhow well the current knowledge of human brain function translates into thehighly dynamic real world (McDowell, 2014). Therefore, there is a need to studythe brain in ecologically valid environments to truly understand how the humanbrain functions to optimally control behavior in face of ever-changing physicaland cognitive circumstances.To this end, we have developed and validated transformative techniquesand tools to collect laboratory-grade neural, physiological, and behavioraldatafrom unconstrained, freely movingsubjects in everyday environments. We have alsodeveloped and applied state-of-the-artmachine-learning algorithms to find statistical relationships among thevariations in environmental, behavioral, and functional brain dynamics.Thistalk will focus on the development of tools for real-world neuroimagingresearch and the results of sample neurocognitive studies.
本报告适合于对计算神经科学与信息处理感兴趣的计算机、电子、控制、生物医学工程等专业的教师和学生，欢迎广大师生参加！
信息科学与工程学院
2018年10月26日
