<strong>Data Science: Recent Developments and Future Trends</strong>

<strong>Data Science: Recent Developments and Future Trends</strong>

时间：2017年6月7日上午10:00 地点：九龙湖计算机楼4楼会议室413

报告简介：

Data contains science. How data is handled today is much different than the classical mathematical approach of using models to fit the data. Nowadays, people are supposed to find rules and properties within the data set and sometimes among different types of data sets. Data science is about the study of: (1) The science of data, (2) Knowledge extraction from massive data sets (BigData) mainly using machine learning, (3) Data and data set relations, (4) BigData processing including tools such as Hadoop and Spark on cloud computing, and (5) Visualization of massive data and human�computer interaction. In this talk, we will explain data science and its relationship to BigData, cloud computing, and data mining. We also discuss current research problems in data science and provide possible relations to the data science industry. Emphasizing the bridge between computer science and math, we will explain why data science would serve as a tremendous engine to the development of the new computing and math theories. In this talk, we will first quick introduce some basic concepts, and then focus on data mining and machine learning methods such as kNN, k-Means, SVM, PCA, neural networks, and other popular methods. We will selectively discuss the principles of these methods in certain depth. We also introduce timely problems for study including: smart search, the dimension reduction problem, video tracking, and topological data processing. For future research problems, we would like to discuss computing and algorithm design based on various MapReduce-based models. For applications, we provide a simple case study in image segmentation using MapReduce with detailed algorithm analysis. We will give some hands-on examples in Spark using ML library and possibly provide a short introduction to TensorFlow.

报告人简介：

Dr. Li Chen is currently an Associate Professor of computer science at the University of the District of Columbia. He received his BS, MS, and PhD in CS from Wuhan University (1982), Utah State University (1995), and the University of Bedfordshire (2001), respectively. Chen has worked in both academia and industry. He was a lecturer at South East University and Wuhan University in China before serving as a visiting assistant professor at the University of North Dakota, visiting associate professor at the University of Maryland, and adjunct professor at Virginia Tech. In industry, he worked for companies as a senior software engineer. Chen is an ACM Distinguished Speaker. Chen has given professional talks on various topics in many universities and colleges including the University of Toronto, University of Maryland, George Mason University, Rutgers University, NIH, and Georgetown University. He was a visitor of DIMACS (Rutgers-Princeton) and a Scientific Researcher in the Fields Institute at the University of Toronto. Chen's research interests are broad in computer science and applied mathematics and include applied algorithm design, digital and discrete geometry, image processing, and applications to data science. Chen has published more than 65 researcher papers in journals and conference proceedings including Discrete Mathematics; Theoretical Computer Science; IEEE Systems, Man, and Cybernetics; Information Science; the Chinese Science Bulletin; and the Chinese Journal of Computers. Chen has published a total of five books including the recently published “Digital and discrete geometry” (Springer, 2014), “Digital functions and data reconstruction" (Springer, 2012), and “Mathematical problems in data science" (with Su and Jiang, Springer, 2016). Chen has received several awards including the SEAS Teaching Award(UDC, 2017), SEAS Outstanding Research Award (UDC, 2015), and the Award Research Fund of Chinese Academy of Science for Young Scientists (1987). In 2014, Chen chaired the Satellite Conference on Data Science of International Congress of Mathematicians (ICM14). He also holds a United States patent.

计算机网络和信息集成教育部重点实验室（东南大学）