学术报告第201536期

报告题目：An Intelligent Optimization, Clustering and Classification Framework for High Dimensional, Overlapped Classes, and Imbalanced Data
报  告  人：Nian Zhang, Ph.D.
报告时间：2015年6月22日上午10：00
报告地点：南一楼中311室

邀 请 方：“多谱信息处理技术”国家级重点实验室

报告摘要：
        With the continuous expansion of data availability in many large-scale, complex, and networked systems, it becomes critical to advance raw data from fundamental research on the Big Data challenge to support decision-making processes. Classification of data becomes very difficult because of unbounded size and imbalance nature of data. The minority samples are those that rarely occur but are extremely important, and they also imply an overwhelming cost when they are not well classified. Therefore, it is very important to develop novel optimization, clustering and classification algorithms to mitigate the curse of dimensionality, minimize the overlap across clusters from different classes, and intensify the underrepresented class concepts for improved overall performance and less computational time.
        However, developing such intelligent optimization, clustering and classification framework requires significant research on both fundamental understanding of machine learning and data mining and innovative algorithm design. This talk aims to present the state-of-the-art machine learning and data mining methods on big data analysis and the evaluation tools. Specifically, this talk will describe the nature of the class imbalance problem, provides a detailed review of recent research developments to solve the class imbalance problem, including sampling methods, cost-sensitive learning methods, kernel-based learning methods, and active learning methods. Assessment metrics will be presented. The opportunities and challenges for research development in this field will be briefly discussed.

报告人简介：
        Dr. Nian Ashlee Zhang received her B.S. degree in Electrical Engineering at the Wuhan University of Technology, M.S. degree in Electrical Engineering from Huazhong University of Science and Technology, and Ph.D. in Computer Engineering from Missouri University of Science and Technology. She is a faculty member with the Department of Electrical and Computer Engineering at the University of the District of Columbia, Washington D.C., USA. Dr. Zhang's research expertise and interests include computational intelligence, machine learning and data mining, and various application fields including big data science, class imbalance problem, pattern recognition, time series prediction, biomedical applications, and autonomous robot navigation.
        Dr. Zhang is the PI (sole PI) of the U.S. National Science Foundation Grant: “An Intelligent Optimization, Clustering and Classification Framework for High Dimensional, Overlapped Classes, and Imbalanced Data,” 7/2015 – 7/2017, $200K. Dr. Zhang is also the Co-PI of the U.S. National Science Foundation Grant: “Integration, Cultivation, and Exposure to Biomedical Engineering at the University of the District of Columbia,” 7/2015 – 7/2018, $400K. Dr. Zhang’s research was also funded by Office of Naval Research (ONR), NASA, US Geological Survey (USGS), Xerox Corporation, Bush Foundation, and University of the District of Columbia (UDC).
        Dr. Zhang has been selected to be an ONR Summer Faculty Research Fellow (20 selected Fellows out of 600 applicants nationwide) and a Myrtilla Miner Faculty Fellow. She received the Excellence in Teaching Award in 2015 and the Outstanding Faculty Award for outstanding research mentorship in 2014. Dr. Zhang was a recipient of the Best Paper Award in the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), St. Louis, MO, May 25-28, 2003. Dr. Zhang is an Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems, and Guest Editor of Computational Intelligence and Neuroscience Journal and the International Journal of Systems, Control and Communications (IJSCC). She is an IEEE Senior Member, IEEE Computational Intelligence Society’ Neural Networks Technical Committee Member, and Publications Chair of over 20 IEEE sponsored international conferences.