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Zhu Xiaoyan Professor of Department of Computer Science and Technology Tsinghua University Tel: 86-10-62796831 Fax: 86-10-62782266 Email: zxy-dcs@tsinghua.edu.cn Address: Dept. of Computer Science and Technology, Tsinghua University, Beijing 100084, P.R.China Incumbent Positions: Professor and Ph. D. Supervisor of Department of Computer Science and Technology, Tsinghua University Deputy Head of State Key Laboratory of Intelligent Technology and System, Tsinghua University Head of Tsinghua-HP Multimedia Research Lab Deputy Head of Beijing Computer Federation Research Experiences: Visiting Professor at Cornell University, USA, 2006 Visiting Professor at the University California, Santa Barbara, USA, 2002-2003 Visiting Professor at Kyushu University, Japan, 1998 Education: BSc, University of Science and Technology Beijing, 1982 MSc, Kobe University, Japan, 1987 Ph. D., Nagoya Institute of Technology, Japan, 1990 |
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Lecturer Minlie Huang Post Doc Yanmei Chai Xinyu Zhang PhD Candidates Jiao Li Chong Long Zhaocheng Fan Fangtao Li Zhicheng Zheng Fan Bu Hongtao Zhang Feng Jin Master Students Hongning Wang Yang Tang Jinchen Liu |
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* (Fall) Advanced Artificial Intelligence, Graduate Student The course helps students to grasp the essence of AI in both strategies and methods, guiding them to solve problems in the point view of AI other than traditional approaches. The course will introduces the history of AI, describes the correspondent principles, methods and approaches, and keeps track of state of art developments of related fields. By the combination of the above three, students can be greatly benefited in knowledge learning, hot-spots pursuing and finally their capability of dealing with real world problems using AI techniques. * (Fall) Artificial Neural Networks, undergraduate Student This course will provide a comprehensive foundation of neural networks, or artificial neural networks, multidisciplinary nature of the subject, such as learning mechanism, structure, as introductory material in first tow chapters. In the following four chapters, several kinds of typical neural networks are introduced, which are mainly Perceptrons (single layer and multilayer Perceptrons), Self-Organizing Maps (Kohonen network and ART). In the last part, SVM will be introduced as a new type of neural network and relationship with some interrelated areas such AI and Patter Recognition and the application of ANN are mentioned. The purpose of the course is to introduce you to some practical, useful concepts, designs, and algorithms in ANN with a minimum amount of mathematic rigor. * (Fall 1996-1999) Application Technology of AI, undergraduate Student |
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| Pattern Recognition, Neural Network, Machine Learning, Natural Language Processing, Text Mining£¬Q&A System etc. Recent works focus on Intelligent Information Processing on Biomedical Literature. |
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State Key Laboratory of Intelligent Technology and Systems
Email: zxy-dcs@tsinghua.edu.cn