主讲教师：Eric Xing

        Dr. Eric Xing is an associate professor in the Machine Learning Department, the Computer Science Department, the Language Technology Institute, and the Lane Center of Computational Biology within the School of Computer Science at Carnegie Mellon University. His principal research interests lie in the development of machine learning and statistical methodology; especially for solving problems involving automated learning, reasoning, and decision-making in high- dimensional, multimodal, and dynamic possible worlds; and for building quantitative models and predictive understandings of the evolutionary mechanism, regulatory circuitry, and developmental processes of biological systems.

        Professor Xing directs the Laboratory of Statistical Artificial Intelligence and Integrative Genomics (SAILING LAB) at Carnegie Mellon. His current work involves, 1) foundations of statistical learning, including theory and algorithms for estimating time/space varying-coefficient models with evolving structures, sparse structured input/output models in very high-dimensional space, and nonparametric techniques for infinite-dimensional models; 2) computational and comparative genomic analysis of biological sequences, systems biology investigation of gene regulation, and statistical analysis of genetic variation, demography and disease linkage; and 3) application of statistical learning in social networks analysis, social media mining, computer vision, and natural language processing, which are supported by NSF, NIH, DARPA, ONR, AFOSR, Sloan Foundation, etc.

        Professor Xing received his B.S. in Physics from Tsinghua University, his first Ph.D. in Molecular Biology and Biochemistry from Rutgers University, and then his second Ph.D. in Computer Science from UC Berkeley. He has been a member of the faculty at CMU since 2004. He has published over 100 peer-reviewed papers in machine learning, statistics, and computational biology, and is an action editor of the Machine Learning Journal, an associate editor of the Annals of Applied Statistics, and the PLoS Journal of Computational Biology. He is a recipient of the NSF Career Award, the Alfred P. Sloan Research Fellowship in Computer Science, the United States Air Force Young Investigator Award, and best paper awards in a number of conferences including UAI, ACL, and SDM.

【个人主页】  http://www.cs.cmu.edu/~epxing/

主讲教师：Li Fei-Fei

        Dr. Li Fei-Fei is an assistant professor in the Computer Science Department at Stanford University and director of the Stanford Vision Lab. She also holds courtesy appointments in the Neuroscience Program and the Psychology Department at Stanford. Dr. Li Fei-Fei's main research interest is in vision, particularly high-level visual recognition. In computer vision, Fei-Fei’s interests span from object and natural scene understanding to activity and event recognition in both videos and still images. In human vision, she and her students have studied the interaction of attention and natural scene and object recognition, and decoding the human brain fMRI activities involved in natural scene categorization by using pattern recognition algorithms. Work in the Vision Lab is supported by NSF, NIH, DARPA, ONR, Microsoft Research, Google, Kodak, NEC, etc.

        Fei-Fei received her A.B. degree in physics from Princeton University, and subsequently her Ph.D. degree in electrical engineering from the California Institute of Technology. From 2005 to August 2009, Fei-Fei was an assistant professor in the Electrical and Computer Engineering Department at University of Illinois Urbana-Champaign and Computer Science Department at Princeton University, respectively. She joined Stanford in 2009. Fei-Fei has published over 60 peer-reviewed papers in computer vision, cognitive neuroscience and machine learning at top journals and conferences, including Nature, PNAS, PAMI, CVPR, ICCV, NIPS, etc. Fei-Fei is a recipient of a Microsoft Research New Faculty award, an NSF CAREER award, two Google Research Awards, and a CVPR Best Paper Honorable Mention award. (Fei-Fei publishes using the name L. Fei-Fei.)

【个人主页】  http://vision.stanford.edu

联系人

吕宝粮 教授 上海交通大学 blu AT cs DOT sjtu DOT edu DOT cn

薛向阳  教授 复旦大学 xyxue AT fudan DOT edu DOT cn

助教名单

	姓名 池明旻 学历 博士 职称 副教授 研究方向 机器学习 单位 复旦大学
	姓名 路 红 学历 博士 职称 副教授 研究方向 图像视频处理 单位 复旦大学
	姓名 郭跃飞 学历 博士 职称 副教授 研究方向 机器学习，模式识别 单位 复旦大学
	姓名 张 巍 学历 博士 职称 讲 师 研究方向 机器学习 单位 复旦大学
	姓名 李云 学历 博士 职称 副教授 研究方向 模式识别，机器学习 单位 南京邮电大学
	姓名 杨旸 学历 博士 职称 讲师 研究方向 生物信息学， 机器学习 单位 上海海事大学
	姓名 薛贵荣 学历 博士 职称 副教授 研究方向 信息检索、数据挖掘、机器学习 单位 上海交通大学
	姓名 赵海 学历 博士 职称 讲师 研究方向 自然语言处理，机器学习 单位 上海交通大学
	姓名 石立臣 学历 硕士 职称 博士研究生 研究方向 脑-计算机接口、机器学习 单位 上海交通大学
	姓名 纪政 学历 硕士 职称 博士研究生 研究方向 模式识别、机器学习 单位 上海交通大学
	姓名 李沐 学历 学士 职称 硕士研究生 研究方向 机器学习、 脑-计算机接口 单位 上海交通大学
	姓名 连晓晨 学历 学士 职称 硕士研究生 研究方向 计算机视觉、机器学习 单位 上海交通大学