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Ziyu Guan, Professor

School of Computer Science and Technology

Contact Information

Address: 2 South Taibai Road, Xi\\\\'an, Shannxi, China

Email: zyguan@xidian.edu.cn


Ziyu Guan is currently a full professor in Xidian University. His research work is focused on social media computing and pattern recognition, with an emphasis on developing novel machine learning and data mining techniques for exploiting the wisdom of crowd in social media, to solve problems such as classification, recommendation, retrieval, etc. He has published over 70 high quality journal/conference papers, out of which 51 papers were published in leading journals/conferences, such as IEEE TKDE, IEEE TPAMI, IEEE TIP, VLDB, SIGMOD, SIGIR, ICDE, CVPR, WWW, AAAI, IJCAI and SIGKDD. According to Google Scholar, his research work has been cited over 2300 times (h-index 25). In 2015, he acquired a national youth talent title. He is an associated editor of IEEE TKDE, Neurocomputing, the International Journal of Machine Learning and Cybernetics, and Knowledge and Information Systems. He has served or is serving as (senior) program committees members of many leading international conferences, e.g., SIGKDD, AAAI, IJCAI, NeurIPS, ICML, ICLR, SIGIR.


Full CV available at: CV

Working & Education Experience

2017 - present, Xidian University
                         Professor, School of Computer Science and Technology

2014 - 2017, Northwest University of China
                         Professor, College of Information Science and Technology

2012 - 2013, Northwest University of China
                         Researcher, College of Information Science and Technology

2010 - 2012, University of California at Santa Barbara
                         Assistant project scientist, Department of Computer Science
                         Advisor: Prof. Xifeng Yan

2004 - 2010, Zhejiang University
                         PhD in Computer Science and Technology
                         Advisor: Prof. Chun Chen

2000 - 2004, Zhejiang University
                         BS in Computer Science and Technology